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About The Role The role sits at the intersection of model development and production systems: taking ML workloads from prototype to monitored, reliable services running at scale. The team ships models that support real product decisions daily, and this role will own critical pieces of that pipeline - from training and evaluation through deployment, serving, and continuous monitoring - working alongside data scientists, backend engineers, and platform teams. Key Responsibilities Design, train, and evaluate production ML models - classification, ranking, NLP, and recommendation use cases - with clear ownership of accuracy, latency, and cost tradeoffs Build and maintain data pipelines in Python and PySpark/Spark for feature engineering, training datasets, and online/offline consistency Deploy models end-to-end using AWS SageMaker, Vertex AI, or Kubernetes-based serving stacks, including canary releases, shadow deployments, and rollback procedures Instrument model monitoring for data drift, feature skew, and performance regression; build automated alerting and retraining triggers Optimize inference performance: batching, quantization, distillation, and hardware-aware serving for latency-sensitive workloads Collaborate with data scientists and MLOps engineers to establish experiment tracking, model versioning (MLflow or equivalent), and reproducible training workflows Contribute to code reviews, architecture discussions, and ML engineering best practices across the team What We Are Looking For 3–6 years of experience in machine learning engineering or applied ML, including multiple production model deployments Strong Python engineering skills; comfort with testing, code review, and software engineering fundamentals beyond notebooks Deep proficiency with PyTorch or TensorFlow, plus hands-on experience with scikit-learn and classical ML methods Production experience with at least one major cloud ML platform: AWS SageMaker, GCP Vertex AI, or Azure ML Solid grasp of ML fundamentals: evaluation design, regularization, bias-variance tradeoff, and distribution shift Experience with containerized ML services (Docker, Kubernetes) and workflow orchestration (Airflow, Kubeflow, or Dagster) Bonus: experience with LLM fine-tuning or serving (vLLM, Triton), real-time feature stores (Feast, Tecton), or a Master's/PhD in a quantitative field

Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

At AmaWaterways, we believe meaningful careers begin with purpose, passion and a shared commitment to delivering unforgettable experiences. For those who value curiosity, connection and personal enrichment, AmaWaterways offers the opportunity to help craft meaningful river journeys that invite travelers to follow their own current. Built on a foundation of heartfelt hospitality, we treat our guests—and each other—with genuine care, warmth and respect. AmaWaterways fosters a collaborative environment both onboard our ships and across our global network of offices, where team members grow together, support one another and take pride in upholding the high standards and thoughtful service our company is known for. We invite talented, motivated professionals to explore our career opportunities and begin their journey with AmaWaterways today. Role Summary AmaWaterways is hiring a Data Analytics Engineer to own the analytics layer of our modern data platform. You will design governed data marts, build the semantic layer that powers our scorecards, and partner directly with Finance, Marketing, Revenue Management, Operations, and Reservations to turn ambiguous business questions into trusted models and dashboards. You will work on top of a Snowflake-native warehouse that is actively being built out, alongside a Senior Data Engineer who owns the ingestion plumbing. You will apply software engineering practices to analytics: version control, dbt tests, CI/CD, and clear documentation. You will also be an AI-native practitioner. Our daily environment is Claude Code, Snowflake Cortex, and dbt Cloud, and we expect you to use them fluently, not curiously. What You Will Build Governed semantic models in dbt for our top business KPIs: bookings, occupancy, revenue, cancellations, retention, marketing performance, and operations metrics. Marts and reporting views on top of our medallion warehouse (Bronze, Silver, Gold, Reporting), with strict typing and clear grain documentation. Tableau and Power BI assets that share a single source of truth in the warehouse. No off-platform calculations. Cortex Analyst semantic YAML for natural-language data exploration by our internal users. Data quality tests on every model you author, with clear ownership of the freshness and accuracy SLAs. Companion views for the AMA Pulse scorecard (currently 72 KPIs across 894,000 rows of historical sailings). BI assets that consolidate analytical work currently spread across the AMA Pulse Streamlit app, Tableau Cloud, and ad-hoc SQL. Day To Day Responsibilities Modeling and SQL Build dbt models in our medallion layout. Use staging, intermediate, and mart models with explicit grain. Use SCD2 snapshots where business questions span time. Write performant SQL in Snowflake. Read query profiles when something is slow. Use clustering and warehouse sizing deliberately. Apply consistent naming conventions and audit columns across every mart. Semantic layer and metric governance Define metrics in the dbt Semantic Layer with explicit dimensions, time grains, and ownership. Author Cortex Analyst semantic YAML for the marts that internal teams query through natural language. Maintain a single canonical definition for every business KPI. No duplicate metric logic across Tableau, Power BI, and Streamlit. BI development and governance Build, optimize, and govern dashboards in Tableau Cloud and Power BI. Implement row-level and object-level security, usage monitoring, and deployment workflows. Audit and modernize legacy BI assets. Retire reports that nobody opens. Data quality and reliability Write dbt tests on every model: not-null, unique, relationships, accepted values, and custom business rules. Add freshness checks and Snowflake Alerts to your gold and reporting models. Track SLAs for the marts that feed leadership-facing reporting. Stakeholder partnership Translate ambiguous requests from Finance, Marketing, Revenue Management, Operations, and Reservations into models the rest of the team can also build on. Write the kind of documentation your future self will want to read. Partner with the Senior Data Engineer to make sure the source pipelines you depend on are designed correctly upstream. AI-native analytics engineering Use Claude Code as your primary working environment, including our shared data-team-skills plugin library. Use Snowflake Cortex (Complete, Search, Analyst) to build natural-language interfaces, summarize text columns, classify free-text, and accelerate exploratory analysis. Use multi-model review through zen-mcp when you are designing a new metric definition or auditing a complex SQL refactor. Required Qualifications 4+ years building governed analytics models and BI assets in a modern data warehouse. Strong SQL on Snowflake. You can write window functions, recursive CTEs, and incremental MERGE patterns without searching the docs. Production dbt experience: models, tests, snapshots, documentation, and CI runs. Tableau (required) and Power BI (strongly preferred) at production quality, including parameterized dashboards, row-level security, and performance tuning on Snowflake-backed extracts or live connections. Git and GitHub workflows with code review discipline. You already use Claude Code, Cursor, or equivalent agent tooling daily, with concrete examples of what you ship faster because of it. Strong written communication. You can explain a metric definition to a Finance leader and a SQL pattern to an engineer in the same week. Strongly Preferred dbt Semantic Layer. Snowflake Cortex Analyst or Cortex Search in production. GitHub Actions CI/CD for dbt projects. Python for data work (pandas, snowflake-snowpark-python, ad-hoc scripting). Domain experience in travel, hospitality, cruise, or consumer finance. Nice to Have Streamlit in Snowflake. Salesforce Data Cloud or Salesforce Marketing Cloud reporting. Power Automate flows for alert and notification routing. Familiarity with Seaware, Oracle, or other reservation system data models. Finance domain depth: revenue recognition, occupancy denominators, AOP targets.

We appreciate your interest in employment with The Honest Company! The Honest Company is committed to a policy of equal employment opportunity, and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally-recognized protected basis under federal, state, or local law. Applicants with disabilities who need assistance with the application process may be entitled to a reasonable accommodation in accordance with applicable law. If you need assistance in completing this application or with the application process because of a disability, please contact the Human Resources Department at 1.888.862.8818 or 1.310.857.3020. About Us The Honest Company (NASDAQ: HNST) is a personal care company dedicated to creating cleanly-formulated and sustainably-designed products spanning categories across diapers, wipes, baby personal care, beauty, apparel, household care and wellness. Launched in 2012, the Company is on a mission to challenge ingredients, ideals, and industries through the power of the Honest brand, the Honest team, and the Honest Standard. For more information about the Honest Standard and the Company, please visit www.honest.com. Our Mission We're on a mission to empower people to live happy, healthy lives. We're a wellness brand with values rooted in consciousness, community, transparency, and design. Every day and in every way, we hold ourselves to an Honest standard. We believe that it is our responsibility to do our part to help create a healthy and sustainable future for all. The Role The Honest Company is seeking a Senior Analytics Engineer. Our centralized data function runs on Redshift, Airflow, dbt, Metabase, and Hex, and the curated layer is now the expected foundation for analytics. As a Senior Analytics Engineer, you own a full domain of that layer, such as supply chain or syndicated consumption data, from source contract to certified mart. You are the person stakeholders in that domain go to when a number is disputed. You frame ambiguous requests before anyone writes SQL, decide how the domain should be modeled, and raise the craft of the analysts and engineers working around you. What you'll do Own one or more domains end to end: ERP orders, shipments, inventory, and cost, or Circana syndicated data, including the cross-domain joins behind SIOP and forecast-accuracy reporting. Write design docs for domain-scale changes, such as a new conformed dimension or an incremental rebuild strategy, and get them reviewed before building. Run definition sessions with supply chain planners and finance analysts; document the agreed definition and bring unresolved conflicts to the Data Council with a recommendation. Define dataset tiers and SLAs for your domain, and lead incident response and post-incident review when those datasets break. Own runtime and Redshift cost for your domain's models; find and fix the expensive ones. Agree schema and quality expectations with Data Engineering for your domain's sources, and hold the line when upstream changes would break them. Shape your domain's backlog with the Sr Manager; say no to work with clear reasons and an alternative. Mentor analytics engineers and analysts; use code review to teach the reasoning behind standards, not only the standards. Lead the migration of your domain's reporting off spreadsheets and raw tables onto curated models. Run interview rounds and help calibrate candidates. What we're looking for Required 6+ years in analytics engineering, data engineering, or a heavily technical analyst role, including at least 2 years owning models that other teams depended on in production. Everything in the Analytics Engineer profile, at a level where others copy your patterns: expert SQL on a columnar warehouse, production dbt (tests, macros, snapshots, exposures, CI), and dimensional modeling across multiple sources. A track record of designing, not just implementing: you can show a modeling decision you made, the alternatives you rejected, and why. Experience resolving a metric definition that two teams disagreed on, and making the resolution stick. Experience owning reliability for datasets with real consumers: tests, freshness, alerting, and incident follow-through. Clear technical writing: design docs, PR descriptions, and documentation a business user can read. Evidence of making others better: mentorship, review culture, or standards adoption you drove. Preferred CPG, retail, or consumer goods experience, especially syndicated measurement data (Circana/IRI, NIQ, SPINS) or retailer vendor portals. Working knowledge of the SIOP/S&OP cycle or the finance close calendar, and how data timing affects them. Experience with a semantic layer, metric store, or data observability platform (Monte Carlo, Datafold). Python; exposure to Airflow, Fivetran, or dlt. What success looks like at 12 months Your domain's reporting runs on curated models, and its spreadsheets of record are retired. Your domain's critical datasets meet their SLAs, and incidents end with a fix to the cause. Stakeholders in your domain bring definition questions to you before they build their own version. At least one other engineer or analyst ships work in your domain to standard without your review. Compensation The pay range for this role is $135,000 - $154,000. Actual compensation is based on many factors including but not limited to depth of experience, skill level, ability, knowledge, education, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total rewards package for this position may also include base, annual incentive plan, benefits, retirement plan, equity, and Employee Stock Purchase Plan. Benefits & Perks At Honest, we're all about investing in our people. We're dedicated to providing a benefits package that supports your well-being, growth, and balance. Check out our benefits and perks we offer to help you thrive both in and out of the office: Comprehensive Health & Wellness 🏥: We've got you covered with top-tier health, dental, and vision plans to keep you and your family feeling great. 401k with Company Match 💰: Your future matters to us. We match your 401k contributions to help you secure a strong financial future. Wellness & Fitness 💪: Stay healthy with a monthly fitness reimbursement and, for those in our Playa Vista office, an onsite gym to keep you active and energized. Work-Life Balance ⚖️: We value your time. We provide a generous and flexible vacation policy to relax, recharge, and spend time on what matters most. Family-Friendly Leave 👶: Growing your family? We offer generous maternity and paternity leave to support you during this exciting journey. Ownership & Equity 💼: Ownership isn't just a mindset here—it's real. Every full time employee is granted equity, giving you a direct stake in our future. When we win, you win. Education Reimbursement 🎓: We're committed to your growth—whether it's for professional development or a new passion, we offer education reimbursement to help you learn and level up. Pet Insurance 🐾: We love your furry family members too! Our pet insurance ensures your pets are taken care of, because they're part of the family. Please note: Benefits offerings may vary based on the position and geographic location. California Privacy Rights Notice for Californian Job Applicants and Prospective Talent Effective Date: January 1, 2020 Under the California Consumer Privacy Act of 2018 ("CCPA"), The Honest Company, Inc. ("Honest" or "us" or "we") is required to inform California residents who are our job applicants or prospective talent (together "job applicants" or "you") about the categories of personal information we may collect about you and the purposes for which we use this information. Click here if you are a California resident to read disclosures required by the CCPA. Note this notice applies only to personal information that is subject to the CCPA. Categories of Personal Information We Collect. We may collect the following categories of personal information about our job applicants, who are California residents: Name Signature Social Security Number Email and mailing address Telephone number Education Employment history How We Use Job Applicants' Personal Data. We use and disclose the personal information we collect for our business purposes. These business purposes include, without limitation: Processing evaluating your application to determine your qualifications for the role to which you've applied, and communicating with you about your application, including to check references or your background, and communicate with you about other jobs that may interest you. Other business purposes as identified in the CCPA, which include: Auditing related to our interactions with you; Legal compliance Detecting and protecting against security incidents, fraud, and illegal activity; Debugging; Performing services for us, such as analytics; Internal research for technological improvement; and Internal operations. Other Interactions with The Honest Company. More information about our privacy practices can be found in our Privacy Policy, which is incorporated herein by reference. Contact Us. For questions or concerns about our Privacy Policy, please contact us at privacy@honest.com.

Job Description: Accelerator, a global Division of Mars Snacking, is on the front line of unlocking growth across high-potential categories and brands to fuel what's next for Snacking. It's home to both emerging and enduring brands, including KIND, TRÜ FRÜ, NATURE'S BAKERY, RXBAR, EGGO, POP-TARTS and RICE KRISPIE TREATS. Combining the scale of Mars with the agility of a start-up, our Division has the ambition to accelerate the future of snacking by delivering products consumers love today, discovering category-shaping innovations for tomorrow and developing entrepreneurial teams whose impact will last for generations. We're looking for passionate talent who dare to dream big, agile collaborators who talk straight and decide fast, and driven performers with a growth mindset. We're proudly part of Mars, while also building something boldly different. If this inspires and energizes you, you've found the right place where you can do cool things with fun people for one of the biggest snacking companies in the world! As an Analytics and Intelligence Engineer , you will be a key member of our collaborative Data and Analytics team, contributing directly to the design, development, and enhancement of Mars Accelerator division reporting, semantic modelling, and intelligence capabilities. You will partner alongside fellow engineers, data scientists, and business stakeholders across sales, marketing, supply chain, and finance to turn complex business requirements into dependable analytical data models and actionable dashboards. In this role, you will help bridge business needs with robust data engineering practices, building high-quality data products, integrating predictive and automated intelligence into analytical workflows, and contributing to the continuous improvement of our modern analytics stack. What You'll Do Partner with cross-functional business stakeholders and engineering peers to build consistent KPI dashboards, reliable data assets, and high-impact reporting tools. Build, test, and maintain robust, scalable data models and semantic layers (using Star Schemas, dbt, and Databricks) that serve as a dependable single source of truth for the Mars Accelerator Division. Collaborate with data scientists and analytics peers to incorporate predictive models, statistical forecasting algorithms, and anomaly detection into business-facing dashboards and semantic layers. Actively follow modern software engineering best practices for data, including version control with Git, collaborative code reviews, automated testing (e.g., dbt tests, data quality validation), and continuous integration (CI/CD). Create well-documented, certified datasets and provide guidance and technical support to business users to help them self-serve data with confidence. Maintain high standards for data accuracy, testing, and cataloguing (e.g., Databricks Unity Catalog) to ensure enterprise data remains governed, accessible, and compliant. Act as a hands-on technical resource for BI platforms (e.g., Power BI, Tableau), developing performant, intuitive dashboards and participating in peer reviews to maintain high visual and performance standards. Participate in agile planning, sprint execution, and backlog refinement, delivering well-scoped analytics solutions on time. You Are… An Analytical Problem Solver: You enjoy untangling complex data challenges, exploring patterns, and translating business questions into reliable analytical models. A Team Player & Collaborator: You thrive working within an agile team of engineers, sharing knowledge openly, giving and receiving constructive code reviews, and learning from peers. Quality & Automation-Focused: You take pride in writing clean, well-tested code and automating repetitive workflows. Curious & Adaptable: You stay curious about new tools, approaches, and CPG trends, adapting comfortably as business needs evolve. Qualifications & Experience 3–6+ years of hands-on experience in analytics engineering, business intelligence, or data analytics, delivering reliable data models and production dashboards. Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, Business Analytics, or related field (or equivalent practical experience). Core Technical Skills: Strong proficiency in SQL; experience building and optimizing dimensional models (Star Schemas) and analytical tables. Practical experience with modern data transformation and lakehouse tools, such as dbt, Databricks, Snowflake, or Azure Data Services. Hands-on experience developing intuitive, performant dashboards in platforms such as Power BI or Tableau. Working knowledge of Python or R for exploratory analysis, data transformation, or automation. Familiarity with Git workflows, pull requests, and automated testing frameworks (e.g., dbt test). Exposure to data cataloguing/governance tools (e.g., Unity Catalog) and workflow orchestration (e.g., Databricks Workflows, Airflow, or Azure Data Factory). Experience working within CPG, retail, DTC, or manufacturing environments is a plus. What can you expect from Mars? Work with diverse and talented Associates, all guided by the Five Principles. Join a purpose driven company, where we're striving to build the world we want tomorrow, today. A strong focus on learning and development support from day one, including access to our in-house Mars University. An industry competitive salary and benefits package, including company bonus. #Marsjobs The base pay range for this position at commencement of employment is between the range listed below, however, base pay offered may vary depending on multiple individualized factors, including but not limited to job-related knowledge, skills, and experience. The total compensation package for this position will include variable pay, medical and dental benefits, participation in 401k plan, and paid time off benefits. Details of participation in these benefit plans will be provided if an applicant receives an offer of employment. The pay range shown is applicable to all US locations listed within the job posting:USD 119,040.00 - USD 163,680.00

We appreciate your interest in employment with The Honest Company! The Honest Company is committed to a policy of equal employment opportunity, and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally-recognized protected basis under federal, state, or local law. Applicants with disabilities who need assistance with the application process may be entitled to a reasonable accommodation in accordance with applicable law. If you need assistance in completing this application or with the application process because of a disability, please contact the Human Resources Department at 1.888.862.8818 or 1.310.857.3020. About Us The Honest Company (NASDAQ: HNST) is a personal care company dedicated to creating cleanly-formulated and sustainably-designed products spanning categories across diapers, wipes, baby personal care, beauty, apparel, household care and wellness. Launched in 2012, the Company is on a mission to challenge ingredients, ideals, and industries through the power of the Honest brand, the Honest team, and the Honest Standard. For more information about the Honest Standard and the Company, please visit www.honest.com. Our Mission We're on a mission to empower people to live happy, healthy lives. We're a wellness brand with values rooted in consciousness, community, transparency, and design. Every day and in every way, we hold ourselves to an Honest standard. We believe that it is our responsibility to do our part to help create a healthy and sustainable future for all. The Role The Honest Company is seeking a Senior Analytics Engineer. Our centralized data function runs on Redshift, Airflow, dbt, Metabase, and Hex, and the curated layer is now the expected foundation for analytics. As a Senior Analytics Engineer, you own a full domain of that layer, such as supply chain or syndicated consumption data, from source contract to certified mart. You are the person stakeholders in that domain go to when a number is disputed. You frame ambiguous requests before anyone writes SQL, decide how the domain should be modeled, and raise the craft of the analysts and engineers working around you. What you'll do Own one or more domains end to end: ERP orders, shipments, inventory, and cost, or Circana syndicated data, including the cross-domain joins behind SIOP and forecast-accuracy reporting. Write design docs for domain-scale changes, such as a new conformed dimension or an incremental rebuild strategy, and get them reviewed before building. Run definition sessions with supply chain planners and finance analysts; document the agreed definition and bring unresolved conflicts to the Data Council with a recommendation. Define dataset tiers and SLAs for your domain, and lead incident response and post-incident review when those datasets break. Own runtime and Redshift cost for your domain's models; find and fix the expensive ones. Agree schema and quality expectations with Data Engineering for your domain's sources, and hold the line when upstream changes would break them. Shape your domain's backlog with the Sr Manager; say no to work with clear reasons and an alternative. Mentor analytics engineers and analysts; use code review to teach the reasoning behind standards, not only the standards. Lead the migration of your domain's reporting off spreadsheets and raw tables onto curated models. Run interview rounds and help calibrate candidates. What we're looking for Required 6+ years in analytics engineering, data engineering, or a heavily technical analyst role, including at least 2 years owning models that other teams depended on in production. Everything in the Analytics Engineer profile, at a level where others copy your patterns: expert SQL on a columnar warehouse, production dbt (tests, macros, snapshots, exposures, CI), and dimensional modeling across multiple sources. A track record of designing, not just implementing: you can show a modeling decision you made, the alternatives you rejected, and why. Experience resolving a metric definition that two teams disagreed on, and making the resolution stick. Experience owning reliability for datasets with real consumers: tests, freshness, alerting, and incident follow-through. Clear technical writing: design docs, PR descriptions, and documentation a business user can read. Evidence of making others better: mentorship, review culture, or standards adoption you drove. Preferred CPG, retail, or consumer goods experience, especially syndicated measurement data (Circana/IRI, NIQ, SPINS) or retailer vendor portals. Working knowledge of the SIOP/S&OP cycle or the finance close calendar, and how data timing affects them. Experience with a semantic layer, metric store, or data observability platform (Monte Carlo, Datafold). Python; exposure to Airflow, Fivetran, or dlt. What success looks like at 12 months Your domain's reporting runs on curated models, and its spreadsheets of record are retired. Your domain's critical datasets meet their SLAs, and incidents end with a fix to the cause. Stakeholders in your domain bring definition questions to you before they build their own version. At least one other engineer or analyst ships work in your domain to standard without your review. Compensation The pay range for this role is $130,000 - $150,000. Actual compensation is based on many factors including but not limited to depth of experience, skill level, ability, knowledge, education, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total rewards package for this position may also include base, annual incentive plan, benefits, retirement plan, equity, and Employee Stock Purchase Plan. Benefits & Perks At Honest, we're all about investing in our people. We're dedicated to providing a benefits package that supports your well-being, growth, and balance. Check out our benefits and perks we offer to help you thrive both in and out of the office: Comprehensive Health & Wellness 🏥: We've got you covered with top-tier health, dental, and vision plans to keep you and your family feeling great. 401k with Company Match 💰: Your future matters to us. We match your 401k contributions to help you secure a strong financial future. Wellness & Fitness 💪: Stay healthy with a monthly fitness reimbursement and, for those in our Playa Vista office, an onsite gym to keep you active and energized. Work-Life Balance ⚖️: We value your time. We provide a generous and flexible vacation policy to relax, recharge, and spend time on what matters most. Family-Friendly Leave 👶: Growing your family? We offer generous maternity and paternity leave to support you during this exciting journey. Ownership & Equity 💼: Ownership isn't just a mindset here—it's real. Every full time employee is granted equity, giving you a direct stake in our future. When we win, you win. Education Reimbursement 🎓: We're committed to your growth—whether it's for professional development or a new passion, we offer education reimbursement to help you learn and level up. Pet Insurance 🐾: We love your furry family members too! Our pet insurance ensures your pets are taken care of, because they're part of the family. Please note: Benefits offerings may vary based on the position and geographic location. California Privacy Rights Notice for Californian Job Applicants and Prospective Talent Effective Date: January 1, 2020 Under the California Consumer Privacy Act of 2018 ("CCPA"), The Honest Company, Inc. ("Honest" or "us" or "we") is required to inform California residents who are our job applicants or prospective talent (together "job applicants" or "you") about the categories of personal information we may collect about you and the purposes for which we use this information. Click here if you are a California resident to read disclosures required by the CCPA. Note this notice applies only to personal information that is subject to the CCPA. Categories of Personal Information We Collect. We may collect the following categories of personal information about our job applicants, who are California residents: Name Signature Social Security Number Email and mailing address Telephone number Education Employment history How We Use Job Applicants' Personal Data. We use and disclose the personal information we collect for our business purposes. These business purposes include, without limitation: Processing evaluating your application to determine your qualifications for the role to which you've applied, and communicating with you about your application, including to check references or your background, and communicate with you about other jobs that may interest you. Other business purposes as identified in the CCPA, which include: Auditing related to our interactions with you; Legal compliance Detecting and protecting against security incidents, fraud, and illegal activity; Debugging; Performing services for us, such as analytics; Internal research for technological improvement; and Internal operations. Other Interactions with The Honest Company. More information about our privacy practices can be found in our Privacy Policy, which is incorporated herein by reference. Contact Us. For questions or concerns about our Privacy Policy, please contact us at privacy@honest.com.

What To Expect We are seeking a highly skilled and detail-oriented Manufacturing Accounting Data Engineer to join our team at Tesla. In this role, you will leverage your expertise in data engineering, cost accounting and manufacturing systems to build robust data pipelines and infrastructure. You will perform advanced manufacturing variance analytics, monitor and analyze costs, and provide actionable insights to drive efficiency, profitability, and process improvements in our high-volume manufacturing operations. This position enables cross-functional teams to make critical business and operational decisions by transforming large datasets into meaningful KPIs, visualizations, and dashboards. What You'll Do Data Pipeline and Infrastructure Development: Build and maintain data pipelines, databases, and infrastructure using tools like SQL, Python, and CI/CD to automate analyses and support manufacturing accounting operations. Acquire data from primary or secondary sources and ensure data systems empower operational and exploratory analysis Compliance, Audit, and Automation: Ensure compliance with internal policies, accounting standards, and regulations. Support audits by providing documentation and analysis of manufacturing costs. Automate analyses and pipelines to enable production and finance teams to leverage key insights efficiently Cost Analysis and Variance Analytics: Conduct in-depth analysis of manufacturing costs, track actual costs for processes and products, and perform variance analyses to identify deviations, cost-saving opportunities, and process improvements. Monitor cost trends, investigate drivers of fluctuations, and propose corrective actions in collaboration with cross-functional teams Insights and Reporting: Analyze manufacturing data across production lines to extract statistics, identify trends or patterns in complex datasets, and depict insights via innovative dashboards and reports for upper-level management. Drive meaningful improvements to production efficiency and financial reporting Cross-Functional Collaboration and System Improvements: Work closely with Controls, Process, Manufacturing Engineers, Finance, Operations, and other stakeholders to develop manufacturing variances, inventory, and scrap data collection activities, improve reporting tools, and enhance underlying data systems. Identify underutilized data sources and think outside the box to develop new ways to gather actionable insights for business decisions Inventory and Cost Control: Perform inventory analysis to ensure accuracy, identify discrepancies, and optimize control processes. Implement cost control measures, evaluate cost-saving initiatives, and propose strategies to enhance manufacturing efficiency and reduce expenses What You'll Bring Degree in Accounting, Finance, Data Engineering, Computer Science, or equivalent experience. CPA license, MBA, or relevant certifications preferred but not required 2-4 years of experience in data engineering, cost accounting, or a similar role within manufacturing environments, including working with large datasets and Manufacturing Execution Systems Strong technical skills in SQL for data extraction and manipulation, Python for automation, Tableau (or similar) for visualizations, advanced MS Excel, and ERP systems Deep understanding of manufacturing processes, cost accounting principles, financial analysis, cost modeling, and variance analysis Excellent analytical skills, attention to detail, problem-solving abilities, and the capacity to interpret complex data for actionable decisions Ability to thrive in a fast-paced, evolving environment, with strong communication, collaboration, and decision-making skills Benefits Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire: Medical plans > plan options with $0 payroll deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA Healthcare and Dependent Care Flexible Spending Accounts (FSA) 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits Company paid Basic Life, AD&D Short-term and long-term disability insurance (90 day waiting period) Employee Assistance Program Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays Back-up childcare and parenting support resources Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance Weight Loss and Tobacco Cessation Programs Tesla Babies program Commuter benefits Employee discounts and perks program Earned Wage Access: Real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr. Managers levels) , Tesla

Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture. Preferred locations for team members for our Data Platform roles are our San Francisco or Seattle hubs. About Superhuman Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company's products include Grammarly's writing assistance, Docs' collaborative workspace, Mail's inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at superhuman.com and about our values here. The Opportunity As a Data Engineer on the Business Unit (BU) Pod supporting Go , you'll build the pipelines and data models that help us understand how people use Superhuman's proactive AI assistant. You'll work closely with Product, Engineering, and Data Science to give teams the data they need to improve the product and measure its impact. Go helps people where they already work, through conversations, inline suggestions, and built-in and custom agents. Understanding how people use these experiences takes more than counting clicks. Your work will help teams see where users get stuck, which capabilities they find useful, and what brings them back. It will also help connect Go's usage to customer adoption and business growth. You'll own projects and datasets with a clear scope, supported by experienced engineers. Most of your work will focus on production pipelines and reusable data models that teams can use to answer their own questions. You'll also contribute analysis and dashboards when they help move a decision forward. As you learn the product and our systems, you'll have opportunities to take on more complex work. What You'll Do Build and maintain production data pipelines in Databricks that process product events, user activity, and agent interactions across Go. Develop datasets for onboarding, activation, engagement, retention, and conversion so teams can work from consistent metrics. Work with Product, Engineering, and Data Science to define what needs to be measured, improve event logging, and check that new features are represented correctly in downstream data. Make data models easy to understand and use, with clear definitions and documentation that support self-service through analytics and AI tools. Build focused analyses and dashboards when they help partners use the data or make a decision. Connect Go usage with customer and account data to help teams understand adoption, customer value, and Go's contribution to growth and revenue. Keep the datasets you own accurate, up-to-date, and reliable. Add tests and monitoring, investigate discrepancies, and fix the underlying causes. Improve pipeline and query performance, manage compute costs, and make the code you work on easier to maintain. You'll work alongside engineers and partners across Data Platform and Go. We care about understanding the problem, questioning assumptions, and following through when the answer takes some digging. You'll contribute to design decisions and have teammates to turn to as you build your expertise. Qualifications You have 2+ years of experience building and operating production data pipelines, ideally for product analytics or other critical business use cases. You're highly proficient in SQL and have experience writing, debugging, and optimizing transformations in a modern lakehouse or cloud data warehouse such as Databricks or Snowflake. You understand data modeling and warehouse design, and can turn complex source data into tables that others can understand and reuse. You test your work carefully, investigate unexpected results, and trace data issues back to their source. You have experience with workflow orchestration, version control, and deployment practices for data pipelines, using tools such as Databricks Workflows, Airflow, and Git. You use AI-assisted development tools such as Codex, Claude Code, or Cursor, and take responsibility for testing and validating the code they produce. You communicate clearly with technical and nontechnical partners. You can turn a product question into data requirements and explain the assumptions and limitations behind an answer. You're curious about how people use products and how your work can help teams make better decisions. You follow your work through to production, break problems into manageable steps, raise risks and dependencies early, and ask for help when you need it. Nice to have Experience using Python and/or Spark for data transformations, pipelines, or automation. Experience with product or growth analytics, including adoption funnels, retention, conversion, or A/B experiments. Experience working with event logging and behavioral data from web, desktop, or mobile products. Experience supporting AI products or agents, including measuring adoption, interaction quality, reliability, latency, or usage costs. Experience building dashboards or other data tools that product, analytics, and business teams use to answer their own questions. Compensation And Benefits Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more: Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits) Disability and life insurance options 401(k) and RRSP matching Paid parental leave 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time Generous stipends (including those for caregiving, pet care, wellness, your home office, and more) Annual professional development budget and opportunities Superhuman takes a market-based approach to compensation, so base pay may vary by location. Our US locations are categorized into two compensation zones based on proximity to our hub locations. For more information about our compensation zones and locations where we currently support employment, please refer to this page. If a location of interest is not listed, please speak with a recruiter for additional information. Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined by compensation zone and may be modified in the future. We encourage you to apply At Superhuman, we value our differences, and we encourage all to apply—especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada). Compensation Range: $117K - $205K

Let's face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. We can't cram it all in here, but you'll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you've ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it's not for everyone. But for people with fire in their belly, it's a game-changing, career-defining, soul-lifting move. Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture. If that sounds exciting—and the job description below feels like a fit—we really should start talking. We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. Please ensure you can realistically commit to this structure before applying. The Opportunity BetterUp is looking for a Senior Analytics Engineer with experience building data modeling systems within a modern data stack, supported by intelligent data warehousing and adaptable business intelligence systems, to join our team. At BetterUp we believe data is critical to our success and this role on the Analytics Engineering team will be crucial to this strategy of delivering exceptional data products that will drive key business decisions. If you are passionate about helping people reach their potential, thrive in a fast-paced startup environment where you get to build the future, and love data then this is the role for you. What You'll Do Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making. Build and maintain ELT pipelines from source systems to data warehouses. Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale. Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality. Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship. Contribute towards a robust data security strategy protecting sensitive information and content. Solve critical business problems through the application of programming, optimization, automation, and analytical skills. If you have some or all of the following, please apply: Minimum 5+ years of relevant experience in data engineering and/or analytics engineering Advanced SQL skills with 5+ years of deep experience with Snowflake or similar DB Expertise with data modeling and ETL/ELT (dbt preferred, pipeline development a plus) Seasoned developer (5+ years) within a modern business intelligence tool (Looker preferred) Experience applying software engineering principles (testing, version control, code reviews, CI/CD, etc.) in your working process, to scale analytical development Proven track record of working with data teams in a fast-paced, startup environment Proven track record of successfully working cross-functionally with both technical and non-technical stakeholders Solutions-driven and thrives when given ambiguous, open-ended problems Proven success driving projects through implementation to completion, including stakeholder education and onboarding Obsessed with data protections and privacy (i.e. PII, GDPR, FedRAMP, FIPS, etc.) Hands-on experience using AI tools in your development workflow (e.g., Claude Code, Cursor, AI-assisted dbt and SQL development) AI at BetterUp Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you'll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. As a Senior Analytics Engineer, You'll Architect domain-level AI reinvention: identify the highest-leverage AI opportunities in how we build and scale our data products, secure the resources to test them, and install repeatable mechanisms that lock in proven gains across several teams Build scalable AI-powered systems, such as intelligent pipeline monitoring, automated data quality checks, and AI-assisted development, that change how analytical work gets done across multiple teams Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function We encourage all candidates to share examples of how they've used AI tools in their work—whether it's AI-assisted SQL generation, LLM-powered data documentation, automated anomaly detection, or other applications. We view AI fluency as a complement to craft, not a replacement for it. Benefits At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community. Access to BetterUp coaching; one for you and one for a friend or family member A competitive compensation plan with opportunity for advancement Medical, dental, and vision insurance Flexible paid time off Per year: All federal/statutory holidays observed 4 BetterUp Inner Workdays (https://www.betterup.co/inner-work) 5 Volunteer Days to give back Learning and Development stipend Company wide Summer & Winter breaks Year-round charitable contribution of your choice on behalf of BetterUp 401(k) self contribution We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don't hesitate to reach out — we encourage everyone interested in joining us to apply. BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. The base salary range for this role is as follows: $175,000 – $220,000: New York City and San Francisco $158,000 – $198,000: All other locations We value your privacy. Your personal data will be processed in accordance with our Privacy Policy . If you have any questions about the privacy of your personal data or your rights with regards to your personal data, please reach out to support@betterup.co

Let's face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. We can't cram it all in here, but you'll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you've ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it's not for everyone. But for people with fire in their belly, it's a game-changing, career-defining, soul-lifting move. Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture. If that sounds exciting—and the job description below feels like a fit—we really should start talking. We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. Please ensure you can realistically commit to this structure before applying. The Opportunity BetterUp is looking for a Senior Analytics Engineer with experience building data modeling systems within a modern data stack, supported by intelligent data warehousing and adaptable business intelligence systems, to join our team. At BetterUp we believe data is critical to our success and this role on the Analytics Engineering team will be crucial to this strategy of delivering exceptional data products that will drive key business decisions. If you are passionate about helping people reach their potential, thrive in a fast-paced startup environment where you get to build the future, and love data then this is the role for you. What You'll Do Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making. Build and maintain ELT pipelines from source systems to data warehouses. Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale. Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality. Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship. Contribute towards a robust data security strategy protecting sensitive information and content. Solve critical business problems through the application of programming, optimization, automation, and analytical skills. If you have some or all of the following, please apply: Minimum 5+ years of relevant experience in data engineering and/or analytics engineering Advanced SQL skills with 5+ years of deep experience with Snowflake or similar DB Expertise with data modeling and ETL/ELT (dbt preferred, pipeline development a plus) Seasoned developer (5+ years) within a modern business intelligence tool (Looker preferred) Experience applying software engineering principles (testing, version control, code reviews, CI/CD, etc.) in your working process, to scale analytical development Proven track record of working with data teams in a fast-paced, startup environment Proven track record of successfully working cross-functionally with both technical and non-technical stakeholders Solutions-driven and thrives when given ambiguous, open-ended problems Proven success driving projects through implementation to completion, including stakeholder education and onboarding Obsessed with data protections and privacy (i.e. PII, GDPR, FedRAMP, FIPS, etc.) Hands-on experience using AI tools in your development workflow (e.g., Claude Code, Cursor, AI-assisted dbt and SQL development) AI at BetterUp Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you'll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. As a Senior Analytics Engineer, You'll Architect domain-level AI reinvention: identify the highest-leverage AI opportunities in how we build and scale our data products, secure the resources to test them, and install repeatable mechanisms that lock in proven gains across several teams Build scalable AI-powered systems, such as intelligent pipeline monitoring, automated data quality checks, and AI-assisted development, that change how analytical work gets done across multiple teams Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function We encourage all candidates to share examples of how they've used AI tools in their work—whether it's AI-assisted SQL generation, LLM-powered data documentation, automated anomaly detection, or other applications. We view AI fluency as a complement to craft, not a replacement for it. Benefits At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community. Access to BetterUp coaching; one for you and one for a friend or family member A competitive compensation plan with opportunity for advancement Medical, dental, and vision insurance Flexible paid time off Per year: All federal/statutory holidays observed 4 BetterUp Inner Workdays (https://www.betterup.co/inner-work) 5 Volunteer Days to give back Learning and Development stipend Company wide Summer & Winter breaks Year-round charitable contribution of your choice on behalf of BetterUp 401(k) self contribution We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don't hesitate to reach out — we encourage everyone interested in joining us to apply. BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. The base salary range for this role is as follows: $175,000 – $220,000: New York City and San Francisco $158,000 – $198,000: All other locations We value your privacy. Your personal data will be processed in accordance with our Privacy Policy . If you have any questions about the privacy of your personal data or your rights with regards to your personal data, please reach out to support@betterup.co

About Actively AI Actively AI is defining a new category: Intelligence-Led Revenue. Revenue organizations have always been bottlenecked on human capacity. Reps triage which accounts get attention. Context disappears at every handoff. On any given day, the vast majority of accounts have exactly zero people thinking about them. Actively addresses this at the structural level. Our platform deploys Per-Account AgentsTM across our customers' TAM, working 24/7 to research, identify opportunities, and advance next steps without being asked. Leading enterprises including Ramp, Ironclad, and Samsara are already making this shift. Our co-founders are former Stanford AI researchers, and the team comes from Harvard, CMU, Berkeley, Brex, Scale AI, and Google. We've raised $68M from TCV, First Harmonic, Bain Capital Ventures, First Round Capital, and more. About the Role: We're looking for someone to own data and analytics end-to-end at Actively . This isn't a narrow analyst role — you'll architect the internal systems that help us learn from every customer interaction, GTM workflow, and product signal, and make those insights actionable across the business. You'll work at the intersection of data engineering, analysis, and product thinking — building the tools that help us move fast, learn precisely, and wire insight directly into the AI agents and experiences we ship. What You'll Do: Own internal metrics, dashboards, and reporting across product, GTM, and usage Build systems to track, analyze, and interpret key signals across the customer and product journey Help design and implement internal "sensors" to uncover buried insights Translate messy, real-world data into clean, structured inputs for our reasoning agents Define and evolve our analytics stack — dbt, Snowflake, Mode, etc. — with an eye toward speed and clarity Work cross-functionally with founders, engineering, and forward-deployed teams to prioritize and act on what matters Who You Are: A builder — you like owning problems end-to-end and working from first principles Comfortable with both SQL and Python, and fluent in the modern data stack Analytical by instinct — you've spent enough time with data to develop intuition and taste Bonus: background in math, physics, or quant research Bonus: experience working with GTM teams or building analytics for sales/product workflows Benefits: 🚀 Competitive Early-Stage Equity ⚕ Health, Dental, Vision Coverage 💡 Unlimited PTO + Recharge Days 🍽️ Catered Lunch on Tuesday & Friday w/ Dinners Everyday! 🍿 Fully Stock Kitchen 💻 Cutting-Edge Tech & Tools 🌴 Annual Off-sites & Monthly Events 🚆 Commuter Benefits 🏢 Cozy Office in NYC The base salary range for this full-time position based in New York is: $120,000 - $160,000. This position is eligible for incentive stock options, subject to the terms of Actively AI's applicable plans. Actively AI offers the following benefits for this position, subject to applicable eligibility requirements: health, dental and vision insurance, retirement benefits, and unlimited PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please discuss with your recruiter for more information. Note on Pay Transparency: Actively AI provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Actively AI factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience. Additionally, Actively AI leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Actively.ai reserves the right to modify this information at any time, subject to applicable law. Actively AI is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment without regard to gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other category protected under the law. Actively AI is an equal opportunity employer; committed to a community of inclusion, and an environment free from discrimination, harassment, and retaliation Actively AI provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Actively AI factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience. Additionally, Actively AI leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Actively.ai reserves the right to modify this information at any time, subject to applicable law. Actively AI is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment without regard to gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other category protected under the law. Actively AI is an equal opportunity employer; committed to a community of inclusion, and an environment free from discrimination, harassment, and retaliation. Compensation Range: : $180,000 USD - $210,000 USD Why Join At Actively, you write playbooks rather than follow them. You own outcomes, not just tasks, and see directly how your work changes what customers can do — across a product and go-to-market motion that is scaling fast. The team is high-caliber and low-ego: people who work from first principles, move with urgency, and care deeply about building something that drives real value. If that's the kind of challenge you're looking for, Actively is the right place. Benefits 🚀 Competitive Early-Stage Equity ⚕ Health, Dental, Vision Coverage 💡 Unlimited PTO + Recharge Days 🍽️ Catered Lunch on Tuesday & Friday, Dinners every day! 🍿 Fully Stocked Kitchen 💻 Cutting-Edge Tech & Tools 🌴 Annual Off-sites & Monthly Events 🚆 Commuter Benefits 🏢 Cozy Office in NYC

Ever imagined saying, "I helped launch the future of transportation"? We're rewriting the rules of urban mobility. At Vay, customers tap a button and a car arrives - with no one inside - powered by our world-first Remote Driving technology on real public streets. We're live in Las Vegas and scaling fast, powered by a strategic investment of up to $410 million from Grab. Our mission is simple: replace private car ownership with a faster, cleaner, door-to-door mobility model. If you want to build something real, visible, and genuinely transformative, you'll feel right at home here. What's happening at Vay First to roll out vehicles in both Europe and the USA on public roads without a human being inside & currently the 2nd largest commercial, driverless car fleet in the Western World. We've partnered with Kodiak to bring remote-driving technology to autonomous trucks in the US, showcasing our ability to integrate our system into heavy-duty commercial vehicles and expand the applications of our tech across the US. We've completed over 150,000 trips so far and are busy multiplying our Las Vegas fleet just to meet demand! ...And soon we'll be expanding across the US & Europe 🚀 Why this role is exciting As a Senior Analytics Engineer, you'l be sitting at the core of our Operations team, where data drives day-to-day decisions. You'll work directly with onsite operational leaders to identify opportunities, solve real-world problems, and build analytics products that materially improve performance, efficiency, and customer experience. This is a high-impact, hybrid analytics engineering / business intelligence role. You won't be buried in dashboards no one uses. You'll shape how our customer-facing services operate and scale, with a direct line between your work and operational outcomes. If you want ownership, visibility, and impact, this role delivers all three. What you'll be driving Own end-to-end analytics solutions, from data modeling (SQL, dbt) through to dashboards and insight delivery (Superset, Grafana, Dekart). Act as the primary data partner for Operations and Mobility Product, working closely with Ops and Product leaders to: Identify opportunities Define and refine KPIs Drive continuous performance improvement Deliver measurable impact across critical operational areas including: Fleet readiness Maintenance performance Charging and vehicle positioning optimization Overall operational efficiency Design and maintain self-serve dashboards, alerts, and reporting interfaces that give Ops teams real-time visibility and decision-making power. Translate business and operational questions into actionable, data-driven solutions using strong domain context and product thinking. Collaborate with Data Science teams to align on data practices, tooling, and standards across Vay. Move fast, iterate often, and take ownership, balancing pragmatic delivery with building scalable, long-term data foundations. What are we looking for Strong end-to-end analytics ownership: you've taken data products from concept through to production. Proven track record of impact : your work has directly improved business or operational outcomes. Expert-level SQL skills: complex, performant queries are second nature. Strong experience with dbt: including designing sustainable, reusable data models. Proficiency with BI tools such as Superset, Looker, or similar, and a sharp eye for clear, actionable dashboards. Comfortable working autonomously Experience with cloud data warehouses (e.g. Snowflake, BigQuery). Familiarity with modern data tooling, including: ETL / reverse ETL tools (Airbyte, Hightouch) Data flow / integration tools (NiFi, OpenFlow) Comfortable handling light engineering work, such as: Working with APIs Configuring visualization tools Setting up integrations Solid understanding of time-series data and operational metrics, ideally with exposure to observability or real-time monitoring. Nice to have Experience in fast-paced environments such as startups, scale-ups, or operations-heavy businesses. Familiarity with scripting (Python, JavaScript, etc.) for automation or lightweight tooling. Exposure to operational domains like mobility, logistics, fleet, or marketplaces. A strong product mindset: you think in terms of users, feedback loops, and delivered value, not just queries and pipelines. Why choose Vay 💪 A global team of smart, motivated people from 30+ countries who love tackling hard problems and turning bold ideas into reality 🌍 Huge scope for impact in a fast paced environment 💰 Stock options: A stake in Vay's future - not just a salary 🌴 Flexible Paid Vacation Days 🚗 All Vay team members receive 30% off their Vay rides 🛍️ Exclusive external discounts 💼 $350 Home Office Set-up ✈️ Relocation financial assistance when relocating to Las Vegas 🎊 Regular team events throughout the year For more information on Vay's physical demands, working environments and safety requirements, you can review this link. We'll also cover anything specific to this role during the first interview. We'd love to stay connected for future opportunities, so feel free to include your LinkedIn profile when you apply. We welcome applications from all backgrounds and experiences. If you're excited about shaping something truly groundbreaking, we'd be happy to hear from you. Curious to experience Vay yourself? In Las Vegas? Use the code VAYCANDIDATE for $10 off your first trip in Las Vegas! Download the "Vay" app from the Apple or Google Play store & off you go!