AdTechTalent
Data Science15 days agoHybrid

Criteo

Senior Data Scientist, Commerce Analytics & Insights

data sciencecommerce analyticsanalytics engineeringSQLPythonSparkdata pipelinesmetricsmethodologyanalytical QAdata qualityexperimentationcommercebehavioral data

Key details

Salary

Not specified

Employment type

Permanent Full Time

Seniority

Senior

Years experience

5-10

Location

Barcelona, Spain

Full job description

Senior Data Scientist role focused on leading data and methodological execution for Commerce Analytics and Insights. Responsibilities include building and maintaining data pipelines, ensuring data quality, defining and improving metric methodologies, collaborating with stakeholders to translate business questions into analytical solutions, and driving scalable, reliable analytics workflows. Requires strong skills in SQL, Python, Spark, data engineering, metric design, and experience with large-scale commerce or behavioral datasets. The role supports a hybrid work model based in Barcelona, Spain.

What you'll do

  • Own the data-science and analytical execution layer of Commerce Analytics and Commerce Insights
  • Build, improve, and maintain data pipelines powering recurring analytics and insight generation
  • Develop deep understanding of source tables, data lineage, business logic, and data quality risks
  • Ensure analytical outputs are correct, consistent, and operationally reliable
  • Define, document, challenge, and improve methodologies behind key metrics, cuts, and analytical frameworks
  • Partner with Solution Architect and commercial stakeholders to translate business questions into robust analytical approaches
  • Drive hands-on execution of analyses across commerce analytics and commerce insights use cases
  • Create scalable approaches rather than one-off manual work
  • Investigate and resolve data issues, edge cases, or inconsistencies with strong ownership
  • Contribute to documentation, process improvement, and knowledge transfer to scale work beyond one individual
  • Identify opportunities for automation, standardization, or better data design to improve quality and speed
  • Stay close to business context to align technical execution with client and program needs

Requirements

  • Strong ownership of both execution and quality
  • Comfortable with data engineering and pipelines, analytical logic, and metric design
  • Strong SQL, Python, Spark and coding skills for data processing and workflow development
  • Experience building production-grade or near-production analytical pipelines
  • Experience documenting methods and educating stakeholders on metric definitions and analytical caveats is a plus
  • Ability to understand data tables, their connections, and business interpretation risks
  • Methodologically rigorous with strong judgment on metric definition and validation
  • Ability to translate ambiguous business questions into executable analytical solutions
  • Comfortable collaborating with client-facing and non-technical stakeholders
  • Strategic mindset to improve systems beyond execution
  • Significant experience in data science, analytics engineering, analytical product work, or similar roles in data-rich environments
  • Strong understanding of experimentation, metrics, methodology design, and analytical QA
  • Experience working with large-scale behavioral, commerce, or media datasets

Tech stack

SQLPythonSpark

Benefits

Hybrid working model blending home and in-office experiencesLearning, mentorship, and career development programsHealth benefits, wellness perks, and mental health supportDiverse, inclusive, and globally connected teamAttractive salary with performance-based rewards and family-friendly policiesPotential for equity depending on role and level

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