Junior Data Scientist - Supply Chain Advanced Analytics AI/ML

The Tech Data & AI function includes an Advanced Analytics SCM team, which works hand in hand with the Supply Chain organization on strategically relevant use cases that have the potential to deliver substantial value and redefine the way that the Supply Chain business function operates.

The SCM Advanced Analytics team builds data science products to make supply chain faster, more efficient, and responsive through seamless demand & supply planning, optimized logistics and distribution, customized replenishment, and automated workforce and production planning.

The Assistant Data Scientist is a hands-on role within the SCM Advanced Analytics team, supporting use cases related to Global & Market – Distribution and Outbound excellence. Working under the guidance of a Data Scientist or Senior Data Scientist, the role contributes to data preparation, analysis, modelling, and testing behind data science products, while building the technical depth and business understanding needed to take ownership of a use case.

Key Responsibilities

• Perform data extraction, cleaning, profiling, and exploratory analysis.
• Build and test analytical components, including features, model candidates, calculation logic, and validation scripts.
• Write clear, readable Python and SQL following team standards for version control, code review, and documentation.
• Investigate data quality issues, trace them to source systems, and propose fixes.
• Prepare validation outputs, back-tests, and comparison analyses.
• Support production solutions by running scheduled checks, flagging anomalies, and helping reproduce and resolve issues.
• Produce reusable notebooks, charts, summary tables, and dashboard components.
• Collaborate with distribution centre, outbound, and planning stakeholders to capture requirements and present results.
• Support user testing and enablement sessions and communicate progress and blockers.
• Build technical depth, work in agile delivery cycles, contribute to documentation and knowledge sharing, and ensure regulatory compliance.

Qualifications

• University degree at Bachelor’s or Master’s level in a quantitative discipline such as Computer Science, Data Science, Statistics, Mathematics, Physics, Econometrics, Operations Research, Industrial Engineering, or Supply Chain Engineering.
• Two to four years of professional experience in a data, analytics, or engineering role; relevant internships, working student positions, or substantial applied thesis work are also valid.
• Working proficiency in Python and SQL.
• Grounding in statistics and core data science methods, including regression, classification, clustering, and basic time series.
• Familiarity with Git and notebook environments.
• Exposure to Databricks, Spark, or PySpark is an advantage.
• Fluent written and spoken English.
• Clear communication, curiosity, intellectual honesty, structured working habits, accountability, eagerness to learn, resilience, and a solution-oriented attitude.

This role carries no direct people management responsibility.

Company Culture

At adidas, employees are encouraged to demonstrate courage, ownership, innovation, teamplay, integrity, and respect. The company emphasizes diversity, equity, and inclusion as part of its culture and talent processes.