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Junior Data Scientist - Supply Chain Advanced Analytics AI/ML

Adidas -
Amsterdam

Nu solliciteren

Vacaturegegevens

Fulltime
17 uur geleden

Kwalificaties

Business intelligence
Supplychain
Spark
Git
Engels
Master
SQL
Analytisch vermogen
Bachelor
Communicatieve vaardigheden
Python

Volledige vacaturetekst

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 the data preparation, analysis, modelling, and testing that sit behind our data science products – and builds, over time, the technical depth and business understanding needed to take ownership of a use case.

Key Responsibilities

Hands-on analytical delivery (under guidance)

Perform data extraction, cleaning, profiling, and exploratory analysis in support of active use cases
Build and test analytical components – features, model candidates, calculation logic, validation scripts – against requirements agreed with the responsible Data Scientist
Write clear, readable Python and SQL, following team standards on version control, code review, and documentation from day one
Investigate data quality issues, trace them back to source systems, and propose fixes
Prepare validation outputs, back-tests, and comparison analyses that show whether a solution performs as intended
Support solutions running in production: run scheduled checks, flag anomalies, and help reproduce and root-cause issues
Produce analysis outputs – notebooks, charts, summary tables, dashboard components – that colleagues can pick up and re-run without explanation

Stakeholder collaboration & communication

Join working sessions with DC, Outbound, and planning stakeholders; capture requirements, assumptions, and open questions in a structured way
Ask questions to understand the operational process behind the data rather than taking fields and figures at face value
Present analysis results to the project team and working-level business contacts clearly and honestly, including what the analysis does not show
Support user testing and enablement sessions; collect user feedback and log it for follow-up
Keep the responsible Data Scientist and the Product Owner informed on progress and blockers early

Learning & ways of working

Actively build technical depth in the team’s core stack and working knowledge of distribution centre and outbound processes
Seek out and apply feedback on code and analysis; treat code review as a learning channel
Work in agile delivery cycles: manage own tasks, estimate honestly, and raise blockers early
Contribute to team documentation, reusable components, and knowledge sharing
Ensure compliance with relevant statutory or external regulations and codes of good practice

This role carries no direct people management responsibility.

Key Relationships

Data Scientists and Senior Data Scientists within SCM Advanced Analytics (day-to-day guidance)
Director Product Ownership – SCM Advanced Analytics (line manager)
Global & Market SCM teams – Distribution Centre operations and planning teams
Data engineers and other Advanced Analytics teams
Other teams within Tech (e.g. Data Platforms & Data Governance)

Requisite Education and Experience / Minimum Qualifications

Education

University degree (Bachelor’s or Master’s) in a quantitative discipline (Computer Science, Data Science, Statistics, Mathematics, Physics, Econometrics, Operations Research, Industrial or Supply Chain Engineering, or comparable)

Work experience

2 – 4 years of professional experience in a data, analytics, or engineering role; relevant internships, working student positions, or a substantial applied thesis project are equally valid
Any exposure to supply chain, logistics, manufacturing, or retail operations is a plus, but is not a requirement

Hard skills

Working proficiency in Python and SQL, demonstrated through academic projects, internships, or personal work
Sound grounding in statistics and core data science methods (regression, classification, clustering, basic time-series)
Familiarity with version control (Git) and comfort working in a notebook environment
Exposure to cloud data or lakehouse platforms (Databricks, Spark/PySpark) is an advantage – training will be provided
Able to visualise data and present results clearly; experience with a BI or app framework is a plus
Fluent English (written and spoken)

Soft skills

Clear and to-the-point written and oral communication skills (English)
Genuine curiosity – asks why the numbers look the way they do, and follows the question through
Intellectually honest: reports what the data supports and flags uncertainty rather than smoothing over it
Structured, reliable, and accountable for agreed tasks and deadlines
Eager to learn quickly, act on feedback, and work hands-on with operations teams, including on site
Resilience and a solution-oriented attitude

AT ADIDAS WE HAVE A WINNING CULTURE. BUT TO WIN, PHYSICAL POWER IS NOT ENOUGH. JUST LIKE ATHLETES OUR EMPLOYEES NEED MENTAL STRENGTH IN THEIR GAME. WE FOSTER THE ATHLETE’S MINDSET THROUGH A SET OF BEHAVIORS THAT WE WANT TO ENABLE AND DEVELOP IN OUR PEOPLE AND THAT ARE AT THE CORE OF OUR UNIQUE COMPANY CULTURE: THIS IS HOW WE WIN WHILE PLAYING FAIR.

COURAGE: Speak up when you see an opportunity; step up when you see a need..
OWNERSHIP: Pick up the ball. Be proactive, take responsibility and follow-through.
INNOVATION: Elevate to win. Be curious, test and learn new and better ways of doing things.
TEAMPLAY: Win together. Work collaboratively and cultivate a shared mindset.
INTEGRITY: Play by the rules. Hold yourself and others accountable to our company’s standards.
RESPECT: Value all players. Display empathy, be inclusive and show dignity to all.

At adidas, we strongly believe that embedding diversity, equity, and inclusion (DEI) into our culture and talent processes gives our employees a sense of belonging and our brand a real competitive advantage.

– Culture Starts With People, It Starts With You –

By recruiting talent and developing our people to reflect the rich diversity of our consumers and communities, we foster a culture of inclusion that engages our employees and authentically connects our brand with our consumers.

Job Title: Junior Data Scientist - Supply Chain Advanced Analytics AI/ML

Brand:

Location: Amsterdam

TEAM: Data

State: NH

Country/Region: NL

Contract Type: Full time

Number: 548992

Date: Aug 28, 2026

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