Senior Data Scientist, Commerce Analytics & Insights
Role details
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Job description
We are looking for a senior, strategic, and hands-on Data Scientist to lead the data and methodological backbone of Commerce Analytics and Commerce Insights at Criteo. This person will own the analytical rigor behind the work: building and improving pipelines, understanding source tables and data dependencies, ensuring reliable execution, and defining or validating the methodologies behind key metrics and outputs.
This role is not only about producing analyses. It is about creating trusted, scalable analytical foundations for Commerce Analytics and Insights, while staying close enough to business context to ensure the work remains relevant and useful.
Success in this role means pipelines and analytical workflows are reliable, maintainable, and trusted; metrics are clearly defined, methodologically sound, and consistently applied; and analytical outputs are accurate and resilient enough for repeated commercial use. Data dependencies, assumptions, and limitations should be documented and understood, while manual analytical work should decrease over time as scalable solutions are introduced.
This role is not the primary owner of client orchestration or commercial project leadership. Its center of gravity is data execution, methodological rigor, and scalable analytical foundations.
What You'll Do
- Own the data-science and analytical execution layer of Commerce Analytics and Commerce Insights
- Build, improve, and maintain data pipelines that power recurring analytics and insightgeneration
- Develop deep understanding of source tables, data lineage, business logic, and data qualityrisks
- Ensure analytical outputs are correct, consistent, and operationally reliable
- Define, document, challenge, and improve methodologies behind key metrics, cuts, andanalytical frameworks
- Partner with Solution Architect and commercial stakeholders to translate business questionsinto robust analytical approaches
- Drive the hands-on execution of analyses across commerce analytics and commerce insightsuse cases
- Create scalable approaches rather than one-off manual work whenever possible
- Investigate data issues, edge cases, or inconsistencies and resolve them with strongownership
- Contribute to documentation, process improvement, and knowledge transfer so that work canscale beyond one individual
- Help identify where automation, standardization, or better data design can improve quality and speed
- Stay close to business context so that technical execution remains aligned with client and program needs
Requirements
- Senior and hands-on, with strong ownership of both execution and quality
- Deeply comfortable with data engineering and pipelines, analytical logic, and metric design
- Strong SQL, Python, spark and strong coding skills for data processing and workflowdevelopment
- Experience building production-grade or near-production analytical pipelines
- Experience documenting methods and educating stakeholders on metric definitions and analytical caveats is a plus
- Able to understand what tables mean, how they connect, and where business interpretation can go wrong
- Methodologically rigorous, with strong judgment on how to define and validate metrics
- Structured and practical: you can move from ambiguous business questions to executable analytical solutions
- Comfortable collaborating with client-facing and non-technical stakeholders, even if this is not the center of gravity of the role
- Strategic enough to improve the system, not just execute within it
- Significant experience in data science, analytics engineering, analytical product work, or a similar role in a data-rich environment
- Strong understanding of experimentation, metrics, methodology design, and analytical QA
- Experience working with large-scale behavioral, commerce, or media datasets