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ABOUT QUINCE Quince is a destination for builders, creators, innovators, and operators who want to come together and challenge the status quo. Our mission is simple: make really high quality essentials for really low prices, fairly and sustainably. We deliver on that mission through a unique manufacturer-to-consumer (M2C) model eliminating the layers of traditional retail that add cost and result in consumers paying more than they need to. We find, build relationships with, and work directly with the manufacturing partners behind some of the world's finest products. From there, our teams design smart, efficient operational processes and build and deploy proprietary technology, AI, and analytics to help us scale fast. What began with a small assortment of elevated basics has quickly grown into a cross-category brand spanning apparel, accessories, home goods, and more. Today, tens of millions of people across a growing number of countries come – and return – to Quince because they trust us to deliver. OUR CULTURE Quince is a culture built for builders by builders. Our way of working starts with a blank sheet of paper. We question conventional thinking, use technology and data to uncover new opportunities, and move quickly to turn ideas into reality. We aren't interested in replicating how others do retail. We're building a better way – at a speed and scale unlike anything that's been done before. We dream big and chase the hard problems others shy away from. Rejecting long-held assumptions is part of our company's DNA. Where conventional wisdom says you have to choose – soft or durable, speed or rigor, quality or price – we ask why that trade-off has to exist in the first place. Our pace is fast and the bar is high because our customers expect a lot from us and we refuse to let them down. We believe the best results come from challenging ourselves, learning from one another, and building on each other's strengths. Here, responsibility is not determined by role, tenure, or seniority. Every team member - no matter their level - has the opportunity to drive our business and shape our trajectory. If you're someone who likes to imagine new possibilities and build better systems rather than plug-in to outdated ones, Quince is the place for you. THE IDEAL CANDIDATE The ideal candidate is a self-starter and problem-solver, skilled at leveraging technology and data to deliver top-tier analytics solutions. They thrive on addressing complex business challenges and are consistently effective in making high-judgment decisions at a rapid pace, even in the face of ambiguity and uncharted scenarios. Additionally, the ideal candidate is energized by a work environment where strategy, innovation, and decision-making are intentionally distributed, where transparency, agility, and data-driven insights are highly valued, and where colleagues at all levels hold each other to exceptionally high standards to serve Quince customers. RESPONSIBILITIES: Partner with the US team to understand what exists that we need to replicate and the gaps that we need to build upon Develop and maintain automated reports to track Marketing KPIs: New/Returning Customers, LTV/CAC, Total vs. inc. ROAS Performance Marketing Channel: Paid Social, SEM, App, Affiliates etc. CRM: Customer cohort, Database health + Lifecycle stages Conduct ad-hoc analyses to identify channel inefficiencies, scaling opportunities, areas for improving MER / Total ROAS. Partner with Product, Engineering and Performance team to deliver experimentation and incrementality studies: Geo-Lift tests, Channel Incrementality, Brand lift, MMM validation. Partner with product, engineering and CRM to deliver: A data driven customer lifecycle programme including key drivers of high-value customers A/B and multivariate tests across lifecycle touchpoints that optimize revenue per visit, and Incremental LTV / Revenue A multi-category approach to cross selling, identifying triggers and next best actions based on customer behaviour Implement data quality, governance (inc. GDPR) and AI usage best practices in collaboration with the US. Be an integral part of the international team and contribute to their growth. REQUIREMENTS: Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Data Science, or similar). Master's degree is a plus. 7+ years in a data analytics/product analytics role, ideally with a focus on supply chain within an e-commerce or technology company. Proficiency in SQL and data visualization tools (e.g., Tableau, Looker, Power BIm Mixpanel). Knowledge of statistical analysis and A/B testing; familiarity with Python or R is a plus. Ability to interpret complex data and translate it into actionable insights, with a focus on detail, accuracy, and clarity. Excellent verbal and written communication skills, with the ability to present data insights and recommendations effectively to both technical and non-technical audiences. Demonstrated ability to manage multiple projects and prioritize in a fast-paced, dynamic environment. Based in Berlin / London with the ability to come into the Berlin / London office 4 days per week Preferred Qualifications: Experience in running Geo-lift tests across Europe Previous e-commerce / multi-category experience Strong Performance marketing (attribution) + CRM measurement background Able to translate data analysis into action through storytelling and visualization Understanding of core marketing metrics and how they interact to deliver profitable growth: LTV/CAC, ROAS, MER WHY QUINCE? Joining Quince means being part of a mission-driven team reshaping retail. You will work alongside talented colleagues, tackle meaningful challenges, and contribute to building a more sustainable, accessible future for customers and partners alike. EQUAL OPPORTUNITY & HIRING INTEGRITY Quince provides equal employment opportunities to all employees and applications for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran or military status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Quince is committed to providing reasonable accommodations to qualified individuals with disabilities. If you need a reasonable accommodation to complete your application or to perform the essential functions of a role at Quince, please let us know by completing this accommodation form . We review all requests individually and will work with you to determine appropriate accommodations on a case-by-case basis. Employment is contingent upon successful completion of a background check. Quince will conduct background checks in compliance with applicable federal, state, and local laws. Security Advisory: Beware of Frauds At Quince, we're dedicated to recruiting top talent who share our drive for innovation. To safeguard candidates, Quince emphasizes legitimate recruitment practices. Initial communication is primarily via official Quince email addresses and LinkedIn; beware of deviations. Personal data and sensitive information will not be solicited during the application phase. Interviews are conducted via phone, in person, or through the approved platforms Google Meets or Zoom—never via messaging apps or other calling services. Offers are merit-based, communicated verbally, and followed up in writing. If personal information is requested to initiate the hiring process, rest assured it will be through secure and protected means. Find more English Speaking Jobs in United Kingdom on Arbeitnow

The Gecko platform is the core engine of our product experience. To maintain competitiveness and user satisfaction, we must move beyond surface-level metrics to understand the deep correlations between engine performance and real-world user behavior. We currently face challenges with data quality, such as bot contamination in nightly telemetry, which obscures our understanding of true performance trends. A dedicated analyst is required to bridge the gap between engineering telemetry and actionable product strategy, ensuring that leadership has high-fidelity data to prioritize performance guardrails and technical budgets. Engineering Deliverables Automated Dashboards: Create and maintain high-level overview dashboards that translate complex performance data into consumable formats for Product Managers and leadership. Telemetry Gap Analysis: Audit the Gecko codebase to identify missing collection points or "probes" necessary for a complete understanding of the product experience. Data Sanitization Frameworks: Develop methodologies and tools to identify and filter data inconsistencies, specifically focusing on isolating bot traffic and hardware-specific noise from telemetry streams. Behavioral Inference Reports: Deliver deep-dive analyses correlating technical performance shifts (e.g., LCP, eTLD+1) with user-facing pain points and engagement trends. Scope, Skills, and Effort Estimate Scope The analyst will focus exclusively on Gecko engine telemetry across multiple platforms (Desktop and Android), collaborating with the Performance Team, Data Team, and Product Leadership. Required Skills Technical: Advanced SQL (BigQuery/Redash), proficiency in data visualization using AI tooling, and experience with statistical analysis (e.g., Pearson's correlation, multivariate analysis). Knowledge of Rust/C++ is a strong plus. Strong proficiency with AI tools like Claude Code, Codex, or similar is highly desirable. Domain Knowledge: Ability to understand browser component interactions and their impact on user experience. Soft Skills: Proven ability to work independently, translating technical requirements into business insights. Independent problem solving: Comfortable working in unfamiliar technical problem spaces and figuring out a path forward with minimal guidance, using documentation, experimentation, source code, data, and other available resources . Hiring Ranges: Canada Tier 1 Locations $93,450 — $124,600 CAD Canada Tier 2 Locations $84,600 — $112,800 CAD Hiring Ranges: Remote Germany €62.100 — €82.800 EUR Hiring Ranges: Remote UK £58,500 — £78,000 GBP Find more English Speaking Jobs in United Kingdom on Arbeitnow

The Gecko platform is the core engine of our product experience. To maintain competitiveness and user satisfaction, we must move beyond surface-level metrics to understand the deep correlations between engine performance and real-world user behavior. We currently face challenges with data quality, such as bot contamination in nightly telemetry, which obscures our understanding of true performance trends. A dedicated analyst is required to bridge the gap between engineering telemetry and actionable product strategy, ensuring that leadership has high-fidelity data to prioritize performance guardrails and technical budgets. Engineering Deliverables Automated Dashboards: Create and maintain high-level overview dashboards that translate complex performance data into consumable formats for Product Managers and leadership. Telemetry Gap Analysis: Audit the Gecko codebase to identify missing collection points or "probes" necessary for a complete understanding of the product experience. Data Sanitization Frameworks: Develop methodologies and tools to identify and filter data inconsistencies, specifically focusing on isolating bot traffic and hardware-specific noise from telemetry streams. Behavioral Inference Reports: Deliver deep-dive analyses correlating technical performance shifts (e.g., LCP, eTLD+1) with user-facing pain points and engagement trends. Scope, Skills, and Effort Estimate Scope The analyst will focus exclusively on Gecko engine telemetry across multiple platforms (Desktop and Android), collaborating with the Performance Team, Data Team, and Product Leadership. Required Skills Technical: Advanced SQL (BigQuery/Redash), proficiency in data visualization using AI tooling, and experience with statistical analysis (e.g., Pearson's correlation, multivariate analysis). Knowledge of Rust/C++ is a strong plus. Strong proficiency with AI tools like Claude Code, Codex, or similar is highly desirable. Domain Knowledge: Ability to understand browser component interactions and their impact on user experience. Soft Skills: Proven ability to work independently, translating technical requirements into business insights. Independent problem solving: Comfortable working in unfamiliar technical problem spaces and figuring out a path forward with minimal guidance, using documentation, experimentation, source code, data, and other available resources . Hiring Ranges: Canada Tier 1 Locations $93,450 — $124,600 CAD Canada Tier 2 Locations $84,600 — $112,800 CAD Hiring Ranges: Remote Germany €62.100 — €82.800 EUR Hiring Ranges: Remote UK £58,500 — £78,000 GBP Find Jobs in Germany on Arbeitnow

Soho, London Hybrid working: 3 days in the office Tues - Thurs The Role We are seeking a Senior Data Engineer to join our Data Team, taking a leading role in building the complex, scalable systems that power our data strategy. You will lead architectural discussions, own the design of business-critical data solutions and deliver high-quality systems that bring millions of fans closer to the sports they love. This is a fantastic opportunity to lead the optimisation of our data platforms for real-time AI/ML workloads, mentor engineers and make a significant impact on our business. The Senior Data Engineer leads technical initiatives, maintains data integrity and performance, and works across teams to translate complex business requirements into effective data solutions. The role also uses automation and artificial intelligence to improve efficiency, decision-making and productivity across the organisation. At LiveScore Group, we're the proud home of three of the most exciting brands in the sports and gaming world: LiveScore, LiveScore Bet and Virgin Bet. A fully owned and operated ecosystem that converges the two worlds of sports media and sports betting. We're proud of the high ratings for our commitment to excellence and fueling fan's passion for sport driving us to the top. We don't just lead; we innovate. Our cutting-edge products and immersive experiences set the standard, but it's our people who truly make the difference. Every day, our team embody our values: adaptability, teamwork, a fan-driven approach, and an ever-curious mindset that fuels our ambition. As we scale and continue to create a culture that allows all employees to thrive, we know we need the most talented people with diverse backgrounds, perspectives and skills. If you're good at what you do, come and join us. The more inclusive we are, the more amazing experiences we can create for our users. We know that job descriptions can sometimes seem daunting, and you might not feel you tick every box. But, if you're passionate about the role and have relevant experience, we want to hear from you! Key Responsibilities Lead the design and delivery of robust data pipelines using GCP services such as BigQuery, Dataflow, Pub/Sub and Cloud Storage. This includes integrating data from various sources, ensuring data quality and enabling real-time processing capabilities. Own the design of data models and databases that support business analytics and intelligence, using dimensional data-modelling principles. Select and use GCP database technologies such as Bigtable, Spanner or Firestore to optimise performance and scalability. Lead the automation of data workflows and optimisation of data storage and processing costs within GCP. Use tools such as Cloud Composer for orchestration and establish best practices in performance tuning. Ensure data security by implementing GCP security practices. Manage access controls, comply with data-governance policies and safeguard sensitive information. Work closely with data engineers, business analysts and IT teams to define data requirements and deliver comprehensive data solutions. Provide technical leadership and guidance to team members. Evaluate new GCP features and data-engineering technologies, setting technical direction where they can enhance data infrastructure or enable new data products. Lead the resolution of critical pipeline failures and data-quality incidents, performing fault analysis and ensuring that preventative improvements are implemented. Lead critical system-design and architectural decisions for scalable batch and real-time workloads. Partner with cross-functional teams to translate complex or ambiguous business needs into effective and innovative data solutions. Mentor engineers, review technical designs and foster a culture of continuous learning and engineering excellence. Own improvements to the reliability, performance and cost-effectiveness of data systems. Lead the design and maintenance of robust, secure integrations with core internal systems and critical third-party platforms. Define appropriate monitoring and alerting standards to ensure high system reliability and minimal downtime. Skills, Knowledge and Experience Significant experience in data engineering or data warehousing with large-scale, complex datasets. Advanced SQL and Python skills, with experience using AI-assisted development tools appropriately. Strong knowledge of data-modelling techniques. Deep experience with cloud data services and technologies, ideally within the GCP ecosystem, such as Dataflow, Pub/Sub, BigQuery or Vertex AI. Proven experience designing and implementing robust ELT pipelines, including real-time and large-scale batch processing. Proven ability to deploy and maintain data infrastructure using Infrastructure as Code principles and tools such as Terraform. Experience with Airflow environment management and Docker. Experience contributing to an AI roadmap and evaluating AI tooling, including coding agents, for use within the development lifecycle. The ability to explain complex technical concepts clearly and concisely to technical and non-technical stakeholders. Demonstrable experience applying data-governance, privacy and security best practices in a regulated environment. A proactive and curious approach, with the ability to anticipate and resolve system inefficiencies. The ability to lead cross-functional technical work and translate complex or ambiguous requirements into robust data solutions. A track record of taking end-to-end ownership for the quality, reliability and performance of business-critical data solutions. Experience mentoring engineers and influencing technical standards across a team. What can we offer? Company Performance Bonus Flexible Working Agreements where applicable Private Healthcare Scheme + Employee Enhanced Assistance Enhanced Family Leave - Maternity, Shared Parental & Adoption Leave: up to 6 months at full pay and 6 months at half pay. Paternity leave: up to 4 weeks at full pay Subsidised Gym Membership Annual Travel Card Loan & Ride to Work Scheme Life Assurance (x3 salary) Contributory Pension Plan Virgin Family: Giving you access to exclusive Virgin offers and experiences Thursday drinks in the office and regular socials Find Jobs in United Kingdom on Arbeitnow

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius is looking for a Product Data Analyst. In this role, you'll build and maintain analytical assets that support day-to-day decision-making across the product & business domains . You'll work end-to-end: from shaping raw data into reliable datasets, to creating dashboards stakeholders actually trust to running deeper analyses that clarify what's happening and what to do next. You'll also help develop AI-assisted analytics tools that reduce manual reporting and surface anomalies early. You're welcome to work in our office in Amsterdam Your responsibilities will include: Master Product Analytics data and metrics & provide insights & consultancy to stakeholders and senior Management . from Product & Business domains. Act as their analytical thought partner and data focal point . Dashboard development. Design, implement, document, and maintain interactive dashboards used by business stakeholders. Improve existing dashboards by optimizing usability, performance, and metric definitions. Data engineering support. Contribute to ETL/ELT processes and data modeling: validate sources, monitor data freshness, improve data quality checks, and troubleshoot pipeline issues with clear root-cause writeups. AI-driven analytics. Help design, test, and refine analytical AI agents that streamline reporting, standardize repetitive analysis, and proactively flag anomalies. Participate in evaluation (quality checks, false positives/negatives) and iterate based on feedback. Exploratory and ad-hoc analysis. Translate business questions into analysis plans, apply appropriate statistical methods, and communicate findings clearly (including assumptions, limitations, and recommended actions). Turn recurring ad-hoc requests into reusable assets where possible. Stakeholder collaboration. Clarify requirements, align on definitions (KPIs/metrics), and present results in a way that supports decisions—not just "interesting numbers." We expect you to have: +4 years of experience as a product / business / data analyst Strong proficiency in Python and SQL , and confidence using Excel when it's the fastest tool for the job. You can write readable queries/code and validate your outputs. Solid grounding in statistics and analytical thinking : descriptive statistics, hypothesis testing, regression fundamentals, and the ability to choose the right approach for the question. Experience producing clear, accurate visualizations and explaining what matters in plain language. High attention to detail and data quality mindset : you notice inconsistencies, validate definitions, and build checks instead of relying on hope. Structured problem solving : Turns vague business questions into clear metrics, hypotheses, and actionable analysis. Ownership & accountability : Takes work end-to-end, follows through, and proactively communicates progress/risks. Clear stakeholder communication : Explains insights simply, aligns definitions, and delivers concise summaries people can act on. Communication : Working knowledge of spoken and written English It will be an added bonus if you have: Experience with BI tools (e.g., Tableau, Power BI, Looker, Superset). Familiarity with modern data stacks ( DBT , Airflow, BigQuery /Snowflake/Postgres, etc.). Comfort with experiment analysis / cohort analysis / funnel metrics Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Find Jobs in Netherlands on Arbeitnow

Ort: Zürich Pensum: 80–100 %, Reisebereitschaft vorausgesetzt Stufe: Senior Consultant oder Manager, je nach Erfahrung Make Data Ready for Agentic AI Bei Xebia gestalten wir die Zukunft von Data, AI und Cloud. Mit über 5'000 Expert:innen weltweit unterstützen wir führende Unternehmen dabei, Daten in Wettbewerbsvorteile zu verwandeln und innovative AI-Lösungen erfolgreich umzusetzen. Zur Verstärkung unseres Data- & AI-Teams in Zürich suchen wir eine Persönlichkeit, die Unternehmen mit Migration, Datenprodukten und Data Governance fit für AI und AI-Agenten macht. Im Fokus stehen Banken, Versicherungen und weitere Finanzdienstleister. Du bist Data Consultant und Data Engineer zugleich: Du leitest Engagements und setzt selbst um. Deine Mission Du sorgst dafür, dass die Daten unserer Kunden bereit für AI und AI-Agenten sind. Du leitest Engagements rund um unsere Agentic Data Foundation, vom Readiness Assessment über die Migration, Datenprodukte, Data Governance und Business-Kontext bis zur Umsetzung auf der Plattform, und packst dabei selbst mit an. Dabei arbeitest du eng mit dem Service Line Lead Data & AI, Sales und Business Development sowie unseren Near- und Offshore-Delivery-Hubs zusammen. Deine Aufgaben Analysieren und konzipieren: Agentic Data Readiness Assessments durchführen, Zielarchitektur und priorisierte Roadmap ableiten Migrieren: Data Warehouses und ETL-Strecken mit Xebia Axis auf moderne Plattformen migrieren, vor allem Databricks Datenprodukte und Governance: Datenprodukte mit Data Contracts aufbauen und Governance im Betrieb verankern, z. B. mit Unity Catalog Business-Kontext für AI: Geschäftsbegriffe, Metriken und Ontologien für AI-Agenten nutzbar machen Engagements leiten: Projekte und Delivery-Teams steuern, Angebote mit Service Line Lead und Sales erarbeiten Das bringst du mit Erfahrung: 5+ Jahre im Data-Umfeld, davon mehrere in der Beratung Migration: Praxis in mindestens einer Migration von Data Warehouse oder ETL auf eine moderne Plattform, idealerweise in leitender Rolle Moderne Data-Plattformen: Architektur und Hands-on in produktiven Umgebungen, idealerweise mit Databricks, sowie Spark, SQL, Cloud und Terraform Data Management und Governance: Praxis in Datenmodellierung, Datenqualität und Lineage, mit Blick darauf, was Daten für AI-Agenten nutzbar macht Zertifizierung: Databricks-zertifiziert oder Zertifizierung innerhalb der ersten 3 Monate Kommunikation: Klar und überzeugend mit Kunden und internen Stakeholdern; fliessend Deutsch und Englisch Von Vorteil Weitere Zertifizierungen: Snowflake, Azure, AWS oder CDMP Datenprodukte: Data Contracts (z. B. ODCS), Data Mesh oder Ontologien AI auf Unternehmensdaten: Chat with your Data, Anbindung von Datenprodukten an AI-Agenten (z. B. via MCP) oder AI Ops (Evals, Guardrails) Branche: Banken, Versicherungen oder andere Finanzdienstleister Sprachen: Schweizerdeutsch und Französisch Das macht uns aus 💡 Innovationspotenzial: Bei Xebia liegt der Fokus auf Innovation und Pioniergeist. Du kannst deine kreativen Ideen entwickeln und innovative Gedanken teilen. 🌱 Persönliches Wachstum: Wir glauben an persönliche Entwicklung für herausragende berufliche Erfahrungen. Entfalte dein Potenzial und wachse kontinuierlich. 🤝 Gemeinschaft und Netzwerken: Xebia bildet eine Gemeinschaft von Technologie-Enthusiasten. Triff Fachleute aus verschiedenen Bereichen, teile Wissen und gestalte gemeinsam Innovationen. ⚖️ Flexibilität: Wir schätzen die Work-Life-Balance. Passe deine Arbeitszeit an und finde eine Balance zwischen Karriere und persönlichem Leben. 🎉 Tolle Social-Events: Skitage, spontane Afterwork-Aperos, Weihnachts- und Sommerfeste – wir feiern gemeinsam. Wenn du bereit bist, deine berufliche Reise zu erweitern, heissen wir dich bei Xebia herzlich willkommen. Wir freuen uns auf dich! Find Jobs in Switzerland on Arbeitnow

................ We are looking for an experienced Data Engineer with strong expertise in Apache NiFi to support our client's team in Maulburg, Germany . In this role, you will provide technical expertise in NiFi and help the team implement and manage data-related processes efficiently and reliably. Your Responsibilities : Provide technical support and expertise in Apache NiFi to the client's team Support the implementation and maintenance of data processing workflows using Apache NiFi Analyse and assist with technical issues related to NiFi Work closely with the client's team to ensure smooth operations and effective implementation of requirements Your Profile: Solid experience with Apache NiFi Experience in data engineering and data processing Independent, structured and solution-oriented working style Strong communication skills and the ability to collaborate effectively with a technical team German language skills preferred; English is also an option Find more English Speaking Jobs in Switzerland on Arbeitnow

Our common vision Our mission is to help marketing teams unlock their full growth potential with AI. Our AI-powered attribution creates real transparency, showing how digital advertising investments perform across channels. On that foundation, we optimize budgets so our customers can sustainably grow their bottom line. We support leading European brands across e-commerce, telco, banking, insurance & energy, and many other industries in making their marketing smarter, more efficient, and more impactful. About the role Nexoya runs fully automated, AI-driven budget optimizations and simulations for enterprise marketing portfolios across many ad channels. Every result that reaches a customer must be correct, explainable and on time. As our ML Intern, you make sure it is: you monitor pipeline health, check the quality of predictions, optimizations and simulations, investigate anomalies and turn recurring manual checks into reliable tooling. You work closely with our ML engineers and Customer Success, and you see directly how your work shapes our customers' budget decisions. Your responsibilities Monitor the automation and assure result quality Monitor the automated prediction, optimization and simulation pipelines across customer portfolios and track run health, completeness and timeliness. Verify that predictions, optimization proposals and simulation results meet our quality standards before they reach customers: budget shifts, expected KPI changes, channel constraints and funnel-level effects. Investigate failed or unexpected runs, identify the root cause (data, configuration or model) and resolve it or escalate it with a clear diagnosis. Assure the quality of results over time Define and maintain plausibility checks for optimization and simulation results, for example for budget planning, seasonal shifts or new channel tests. Make sure results are consistent and explainable, so that customers and account managers can trust them without manual checks. Compare optimized and simulated outcomes with realized performance, document deviations and feed the findings back to the ML team. Safeguard data and model quality Monitor input data for gaps, anomalies and tracking changes that affect optimization quality. Track model fit and prediction accuracy per portfolio and flag degradation early. Maintain portfolio configurations such as funnel steps, constraints and target definitions together with the responsible teams. Automate the operational workflow Replace manual checks with Python scripts, validation rules and alerts. Build and maintain dashboards that show run status, data health and model performance across portfolios. Write runbooks so that operational knowledge is shared, not held by one person. The impact you will have Customers receive optimization proposals and simulations that are correct and delivered on time. Issues are caught before customers see them, not after. The time the ML team spends on operational work goes down measurably, because recurring steps are automated. Customer Success can trust automated optimization and simulation results without checking them by hand. Your experience and skills Recently completed Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or a related field. Solid Python skills, including pandas and NumPy, and comfort working with SQL. Good understanding of statistics and basic machine learning concepts such as regression, model evaluation and overfitting. A careful, structured way of working: you check results before you share them and you document what you do. Ability to explain technical findings clearly to non-technical colleagues. Fluent English, spoken and written, is a must. Bonus points Experience with optimization methods, for example constrained or non-convex optimization. Familiarity with Marketing Mix Modeling, attribution or digital advertising metrics. Experience with data pipelines, scheduled jobs or monitoring tools. Experience with Git, Docker and cloud environments. Fluent in German or Italian. Your future work life Purpose: Your work directly influences how enterprise marketers allocate their budgets. Responsibility: You own the quality of a defined part of our automation from day one, with a personal development roadmap and regular feedback. Learning: You work alongside experienced ML and data engineers on production systems, not on side projects. Culture: A transparent company culture at eye level, where every person is valued and supported. Strategy: You take part in shaping company strategy and culture during our quarterly Strategy Days. Events: Regular team events, on-site and off-site. Application process Profile review and short phone screen Take-home case study Case discussion with the ML team On-site interview and team evaluation Find Jobs in Switzerland on Arbeitnow

Shift delivers AI agents that transform insurers' most critical work. By combining deep industry expertise and unmatched data resources, Shift provides proven results that have earned the trust of hundreds of the world's leading insurers. Our insurance-grade AI is accurate, explainable, and secure—empowering human experts to move with unmatched speed, total confidence, and a renewed focus on the people they serve. Your browser does not support the video tag. Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance. Learn more at www.shift-technology.com Shift Technology : Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to transform underwriting, claims, and fraud and risk - driving operational efficiency, exceptional customer experiences and measurable business impact. Trusted by the world's leading insurers, Shift delivers AI when and where it matters most, at scale and with proven results. The Data Science Team 🤖 : The Data Science team works on a broad range of subjects. We actively participate in the definition and development of our suite of products on fraud detection, anti-money laundering and claim automation. We have a lot of technical and professional experience in data science, data engineering, coding, business understanding and client interactions. Additionally, we also work on various data types such as structured data, free text, documents and images. Your key responsibilities will include 🧑‍💻 : Setting up and deploying data processing pipelines, such as data reception (batch or real-time), data cleaning, information extraction, and calibration of fraud detection models. Collaborating with clients to understand their needs and incorporating their feedback to enhance our solutions. Conducting R&D to drive product innovation (machine learning, NLP, image analysis, trend analysis, chatbots, etc.). Supporting the sales team by participating in prospect demos. Partnering in an entire Data Science product lifecycle : Understand how sales, legal, product, engineering are connected together to deliver an AI product to clients. Your profile and requirements ✅ : You are currently enrolled as a master's degree student in either Mathematics, Statistics, Computer Science, Machine learning and/or Big Data. You must be able to provide an internship agreement (Convention de stage) signed by your school or university for 6 months. You have experience in object-oriented programming (OOP) such as prior internship, school and/or personal projects so you can write quality production code. You are comfortable dealing with clients. French is mandatory at a fluent level and you can communicate clearly in English. You can start your internship around February/March 2027 for 6 months. Why join Shift Technology as a Data Scientist Intern ? 🤸‍♀️Flexibility, autonomy and adaptability are part of our core values : We are a horizontal organization without bureaucracy (40% of staff are data scientists) but optimal and reduced line management, focus on delivery and development while having a hybrid model. 🧠Learn from inside an AI leader tech company : Join the 13th French Licorne providing hands on training, workshop and sessions with highly experienced AI research Team. 💶Your commitment, our investment : 2000€ gross monthly gratification, high conversion rate to full time employee, dedicated HR partner, regular reviews and feedback sessions with your team. 🌍Be part of an international and diverse tech firm : Full english speaking environment with 55 different nationalities across the world and 11 offices locations (Paris, Singapore, Tokyo, Sao Paulo, Mexico City, Boston, Madrid, London, Toronto, Berlin...) 🤝Dealing with big clients and developing business skills & knowledge : Real life experience with Insurance business challenges inside the world of AI. What is next ? 🎯 If your application and experience meet our requirements, you can expect : Talent Acquisition interview (30 min) 1st Technical interview(60 min) 2nd Technical interview (60 min) Hiring manager interview (60 min) The interview process can take 2 to 3 weeks, depending on the interviewer's availability. Be sure that we are doing our best to get back to you with an answer as fast as possible. If you are not getting an update on your application after 10 days, please reach out to our email address. To support our permanent, full time employees at every stage of their careers and lives, we provide a competitive total rewards and benefits package. Here are the global benefits we'd like to highlight: Flexible remote and hybrid working options Competitive Salary and a variable component tied to personal and company performance Multiple Learning and Development opportunities, including Focus Fridays, a half-day each month to focus on learning and personal growth Generous PTO and paid holidays Mental health benefits 2 MAD Days per year (Make A Difference Days for paid volunteering) Additional benefits may be offered by country, based on your eligibility - ask your recruiter for more information. Intern and Apprentice positions may receive some of these benefits - ask your recruiter for more details. AI tools are used to help review applications for this role. Read our AI in Recruitment Notice for what the AI considers, how to request a human review, and our most recent bias audit. At Shift we strive to be a diverse and inclusive workforce. We welcome applications from and hire people who will contribute to the diversity of our company, without regard to race, color, religion, marital status, age, national or ethnic origin, physical or mental disability, medical condition, pregnancy, genetic information, gender identity or expression, sexual orientation, or other non-merit criteria. Shift Technology is committed to providing reasonable accommodations for qualified individuals with disabilities in our application and employment process. Should you require accommodation, please email ----- and we will work with you to meet your accessibility needs. Please be aware of scammers and only trust correspondence that comes from emails ending in "shift-technology.com". We will never do initial outreach to you via Whatsapp/Text/SMS, never ask for banking information or personal identification numbers (ex. Social Security Number) as part of our recruitment process. Shift Technology does not accept unsolicited CVs from recruiters or employment agencies in response to the Shift Technology Careers page or a Shift Technology social media post. Any unsolicited CVs, including those submitted directly to hiring managers, are deemed to be the property of Shift Technology. Find Jobs in France on Arbeitnow

Role Summary We are looking for a Senior Databricks Data Engineer with proven hands-on Databricks experience to build, develop and manage STACK's enterprise data platform. This is a production-focused engineering role requiring practical expertise in Databricks, PySpark, Python, SQL and Delta Lake. The role will design reliable pipelines integrating Finance, Delivery, Operations, HR and PMO systems, establish governed and high-quality datasets, and support secure, scalable analytics and reporting. Working with technical and business stakeholders, the successful candidate will take ownership of data engineering solutions and help improve the reliability and performance of the platform. Key Responsibilities: · Design, develop, deploy and maintain production-grade ETL/ELT pipelines using Databricks, PySpark, Python and SQL, integrating APIs, databases, SaaS applications, files and spreadsheets. · Develop and optimize scalable Delta Lake data models and lakehouse architecture for reporting, analytics and future AI use cases. · Build, schedule, monitor and troubleshoot data processing jobs using Databricks Workflows, Lakeflow or Delta Live Tables, as appropriate. · Apply Unity Catalog governance, including access permissions, data ownership, lineage and common data definitions. · Support Databricks workspaces, compute resources, SQL Warehouses, service principals and access management in partnership with relevant technology teams. · Manage development, test and production deployments, monitoring, incident resolution and recovery, using Git and CI/CD practices. · Optimise pipeline performance, Spark processing, compute usage and platform costs while maintaining appropriate security and operational controls. · Implement data quality checks for completeness, accuracy, timeliness, consistency, duplicates and reconciliation with source systems. · Build monitoring and alerting to identify pipeline failures, data quality issues and operational risks. · Integrate reliable, governed Databricks datasets with Power BI and other approved analytical tools. · Work with Finance, Delivery, Operations, HR and PMO teams to translate requirements into sustainable data solutions. · Document pipelines, dependencies, controls and operating procedures, and coordinate specialist external partners when required. Qualifications: · Strong hands-on experience building and supporting production data pipelines directly in Databricks; experience with other cloud data platforms alone is not sufficient. · Practical experience with PySpark, Python, SQL and Delta Lake, including data transformation and performance optimisation. · Experience orchestrating and troubleshooting Databricks data pipelines using Workflows, Delta Live Tables or Lakeflow. · Working knowledge of Unity Catalog, data governance, access controls and data quality practices (Essential). · Experience integrating data from APIs, business applications, databases and files. · Experience supporting Databricks workspaces, compute resources or SQL Warehouses in a production environment. · Experience with Azure data services, Power BI, Git and CI/CD practices. · Understanding of environment management, monitoring, troubleshooting, security and cost control. · Ability to work with non-technical stakeholders, explain data issues clearly and document solutions effectively. · Strong ownership, prioritisation and problem-solving skills. Certifications (Preferred) · Databricks Certified Data Engineer Professional or Databricks Certified Platform Administrator (if available). Find Jobs in United Kingdom on Arbeitnow

About WPP Media WPP is the trusted growth partner for the world's leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth. WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working. For more information, visit wppmedia.com . Role Purpose The Platform Operations Director is responsible for ensuring that solutions developed and released for the Solutions team are operationally ready, properly tested, clearly documented, effectively released, and provide support once live. The role acts as the bridge between delivery, business readiness and BAU operations. It supports the transition of work from project delivery into stable operational use, ensuring that users, stakeholders and support teams understand what has changed, how to use it, how to raise issues, and how ongoing support will be managed with appropriate priority, impact and SLAs This role is particularly important as Solutions Integration moves from a more reactive service model into a structured product and agile delivery function. The Platform Operations Director owns QA, release management, documentation, stakeholder communication, support processes, training, adoption and post-release improvement including BAU bugs and triage. The role works closely with Product Owners, Scrum Master, Engineering, Data, Reporting, QA, Platform Operations, and business stakeholders to make sure delivery does not stop at "built", but continues through testing, launch, adoption, support and measurable operational value. Senior / Specialist-Level Expectations As a Director within the team, this role is expected to help define and improve the operating standards around BAU management, QA coordination, release readiness, business readiness and service transition. Manage and proactively manage risk, resolution SLAs and ensure we are adhering to platform operational best practices. The Platform Operations Director should be able to identify operational risks early, challenge whether a solution is genuinely ready for release, and recommend practical improvements to processes, documentation, testing, support models and stakeholder communications. For smaller initiatives, the role should be able to advise Product Owners and delivery teams on the appropriate level of QA, training, release planning, handover and BAU support required. For larger or more complex initiatives, the role should escalate risks, dependencies or readiness gaps to the Product Manager Lead, Scrum Master, Lead Engineer / Solutions Architect or relevant leadership stakeholders. Key Responsibilities 1. BAU Operations Management Own and coordinate BAU operational processes for assigned platforms, tools, reports, workflows and solutions across all Media solutions. Monitor recurring issues, support trends, operational risks and user pain points. Triage and prioritise BAU requests, incidents, defects and enhancement requests. Ensure BAU work is captured through the agreed intake and backlog process rather than unmanaged emails, verbal requests or fragmented ticket routes. Work with Product Owners and the Scrum Master to distinguish between BAU support, defects, enhancements and new product requirements. Maintain visibility of BAU demand and help identify where recurring issues should become product improvements or engineering fixes. Support continuous improvement of support processes, documentation and operational workflows. This links directly to the team's wider shift away from fragmented request routes and towards clearer delivery rhythms, structured backlogs and improved operational process discipline. The existing documentation notes the need for clearer team rhythms, sprint cadences, retrospectives and mentoring as part of the transition plan . 2. QA Coordination and Testing Readiness Coordinate QA activity across delivery workstreams, ensuring testing requirements are understood before development begins. Work with Product Owners to ensure acceptance criteria, test scenarios and success measures are clearly defined. Support test planning across functional testing, regression testing, data validation, reporting checks and user acceptance testing. Ensure defects are logged, prioritised, tracked and resolved through the agreed delivery process. Work with engineers, analysts and business users to validate that solutions meet functional, operational and reporting requirements. Support the creation of reusable QA checklists, test scripts and validation templates. Ensure solutions are not released without appropriate testing evidence and business sign-off. This is consistent with the Product Owner responsibilities already defined around testing requirements, success criteria, UAT coordination, business validation, release readiness and operational handover . The Platform Operations Specialist would support and operationalise those activities. 3. Business Readiness and Adoption Ensure business users and operational teams are ready to adopt new or changed solutions. Coordinate training, guidance, demos, FAQs, release notes and user communications. Work with Product Owners to identify impacted teams, users, processes and workflows. Confirm that business teams understand what is changing, why it is changing, when it is happening and what action is required. Support stakeholder communications before, during and after release. Gather early feedback from users and ensure issues are captured and prioritised appropriately. Help ensure delivered solutions are embedded into day-to-day operations, rather than remaining underused or misunderstood. The handover documentation highlights the importance of clear communication with users, proper release notes, demonstrations and adoption support for new features and solutions . This role should own the operational discipline around making that happen consistently. 4. Release Readiness and Service Transition Own or coordinate release readiness checklists for assigned solutions. Ensure each release has appropriate testing evidence, documentation, support ownership, training material and stakeholder communication. Coordinate operational handover from delivery teams into BAU support. Confirm that runbooks, troubleshooting guides, known issues and escalation routes are in place. Work with engineering and data teams to ensure monitoring, alerting or manual checks are defined where required. Support go-live planning, release scheduling and post-release hypercare. Track post-release issues and ensure learnings are fed back into future delivery cycles. This role should become the person asking: "Are we actually ready to put this live, support it, explain it, and measure whether it worked?" 5. Documentation and Knowledge Management Maintain clear operational documentation for platforms, reports, tools, processes and workflows. Support the creation of user guides, SOPs, runbooks, release notes, FAQs and support documentation. Ensure documentation is stored in the agreed location and kept up to date. Work with Product Owners, engineers and analysts to document key dependencies, business rules, known limitations and support processes. Help reduce reliance on individual knowledge by making processes and system behaviour transparent. Support onboarding of new team members by maintaining accessible knowledge resources. This is important because the team is moving away from legacy ways of working and informal knowledge transfer into a more structured operating model. 6. Platform and Process Governance Support the consistent use of agreed tools, workflows, ticketing processes and delivery governance. Help ensure work is captured, categorised and progressed through the correct routes. Maintain standards for BAU tickets, defects, release requests, support issues and operational change. Identify process gaps, duplicated effort or inconsistent ways of working. Recommend improvements to BAU processes, support models, QA standards and release governance. Support reporting on operational performance, support demand, defect trends and release readiness. Help ensure changes are controlled, documented and aligned to agreed team practices. This aligns with the documented need to improve proactive behaviour, structured product management, backlog grooming, stand-ups and retrospectives across the team . 7. Stakeholder and Cross-Team Coordination Work closely with Product Owners, Engineering, Data, Reporting, QA, Scrum Master and business users. Coordinate with Activation, Operations, Channel Development, Commercial and other impacted teams where relevant. Ensure operational dependencies are understood and managed before release. Help stakeholders understand support routes, known issues, timelines and release impacts. Escalate operational risks, unresolved defects, readiness gaps or business adoption concerns. Support regular BAU and platform operations updates for leadership where required. The existing Product Owner documentation already describes the importance of coordination across engineering, data, reporting, platform, operations and business teams . The Platform Operations Specialist should provide the operational control layer that supports this. Skills and Experience Essential Experience in platform operations, service transition, QA coordination, business readiness, delivery operations or technical operations. Strong understanding of BAU support processes, release management and operational handover. Experience coordinating UAT, defect tracking, test planning or business validation activity. Ability to create clear documentation, user guides, process notes, release communications and operational runbooks. Strong stakeholder management skills, with the ability to work across technical and non-technical teams. Good understanding of agile or product-led delivery environments. Ability to identify operational risks, readiness gaps, support issues and process improvements. Strong organisational skills and attention to detail. Confident using Jira, Confluence, ServiceNow, Azure DevOps or similar delivery/support tooling. Ability to communicate clearly with users, delivery teams and senior stakeholders. Desirable Experience working in media, advertising, ad tech, martech, reporting, data or platform environments. Experience supporting reporting platforms, dashboards, data products or operational workflow tools. Understanding of data validation, reporting QA or campaign performance data. Familiarity with cloud-based platforms such as GCP, AWS, BigQuery or Snowflake. Experience working with engineering, data engineering or analytics teams. Experience supporting transformation from reactive support models into structured product or agile delivery models. Familiarity with WPP, WPP Media, Choreograph or similar enterprise platform environments would be beneficial. #LI-Promoted Please read our Privacy Notice for more information on how we process the information you provide. Find Jobs in United Kingdom on Arbeitnow

Transforming factory scans into digital reality At RIIICO, we're reimagining how factories adapt to change. Our AI-powered software makes complex production environments editable, interactive, and collaborative, turning manufacturing planning into something anyone can engage with, not just the experts. We're looking for a 3D Data Operator to help power the foundation of our digital factory experiences. No point cloud experience needed, just an eye for detail and curiosity about 3D. In this role, you'll work at the intersection of 3D reality and AI, transforming raw point cloud data into accurate digital twins of real-world production environments. From data preparation to model generation and delivery, you'll help ensure quality, consistency, and continuous improvement across our data pipeline. Your daily work Process 3D scan data (point clouds) and transform it into usable digital factory models using our internal tools and workflows. Run basic pipeline commands for data preparation and AI processing. Configure and verify model outputs to ensure quality, consistency, and usability for downstream applications (e.g., Nvidia Omniverse, Siemens Plant Simulation and others). Collaborate with AI-assisted tools to validate and correct automated results. Flag and troubleshoot anomalies or edge cases in raw or processed data, and document issues clearly (e.g., as Git issues). Track and report your weekly processing output. Continuously improve workflows and documentation based on team feedback and real-world challenges. What we are looking for Strong attention to detail and ability to reliably handle repetitive tasks with care. Self-motivated and dependable: you take responsibility and get things done. Comfortable following defined workflows and standards, and asking for help when something is unclear. Team player with a proactive mindset: you enjoy working in a collaborative team. Fast learner: no prior experience with point clouds required; you're comfortable picking up new tools and workflows quickly. Basic digital literacy: you're confident navigating structured software tools, browser-based interfaces and Microsoft Office. Bonus: Familiarity with 3D environments (e.g., through gaming, CAD, or similar), or a general spatial intuition. English is a must; proficiency in German is a plus for clear communication with the team. Please note: A valid work permit or residence permit for Germany is required for this position. This is a 12-month fixed-term position, with the opportunity to extend or move to a permanent contract based on performance and business development. Benefits Additional vacation days Flexible working hours Hybrid office culture Public transport subsidy Why You Should Join Build something that makes a tangible difference in the world's most important sector: manufacturing. Help shape a product that is being built from first principles. Collaborate with a sharp, hands-on team that values speed, clarity, and ownership. Backed by top international investors and preparing to scale. Find Jobs in Germany on Arbeitnow