Overview
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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 / Incentivos
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 xqbhyrx 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