Overview In this senior, hands-on role you own the data-science and analytical execution layer for Commerce Analytics and Insights. You build scalable pipelines, understand data lineage, and ensure reliable metrics and outputs. Your work creates trusted foundations for scalable analytical products while staying aligned with business questions. You drive methodological rigor, document data assumptions, and reduce manual work through automation, delivering impact for commerce insights.

Compensaciones / Ventajas hybrid work model learning, mentorship & career development health benefits, wellness perks & mental health support diverse, inclusive, globally connected culture competitive salary with performance-based rewards and potential equity

Responsabilidades

Own the data-science and analytical execution layer for Commerce Analytics and Commerce Insights

Build, improve, and maintain data pipelines powering recurring analytics

Understand source tables, data lineage, and data quality risks

Ensure outputs are correct, consistent, and operationally reliable

Define, document, challenge, and improve methodologies behind key metrics and analytical frameworks

Collaborate with Solution Architect and commercial stakeholders to translate business questions into robust analyses

Drive hands-on execution of analyses across use cases

Create scalable approaches over one-off manual work

Investigate data issues and resolve them with strong ownership





Contribute to documentation, process improvement, and knowledge transfer for scalability

Identify automation, standardization, or better data design to improve quality and speed

Stay close to business context to ensure technical execution aligns with client needs

Requisitos principales Senior and hands-on with ownership of execution and quality

Strong data engineering, pipelines, analytical logic, and metric design

Proficient in SQL, Python, Spark and coding for data processing

Experience building production-grade analytical pipelines

Experience documenting methods and educating stakeholders on metric definitions

Ability to understand table meanings, connections, and potential misinterpretations

Methodologically rigorous with judgment in metric definition and validation

Structured and practical, able to translate ambiguous questions into executable solutions

Comfort collaborating with client-facing and non-technical stakeholders

Strategic mindset to improve systems beyond mere execution

Extensive experience in data science, analytics engineering, or similar in data-rich environments

Strong understanding of experimentation, metrics, methodology design, and QA

Experience with large-scale behavioral, commerce, or media datasets ownership and accountability collaboration with stakeholders clear communication

SQL

Python

Spark

📌 Senior Data Scientist, Commerce Analytics & Insights (Barcelona)
🏢 Criteo
📍 Barcelona