Senior Data Scientist — Remote & Data-Driven Supply Chain

Coop Danmark; Albertslund Kommune; Hybrid; DKK 900,000 - 1,200,000; Full time

Benefits offered by this job

Pension

Health insurance

Employee benefits

Work-from-home day

Job summary

Coop Danmark in Albertslund is seeking a Senior Data Scientist for the new Store Partnering team. You will establish a data-driven approach to Coop’s supply chain, turning data into actionable forecasting and planning insights to improve consumer availability across millions daily.

You will lead development of analytics tools, drive ML/AI initiatives in RELEX, and coach analysts, while enabling a data-centric culture across the planning teams.

Qualifications

• 4–6 years of experience with applied ML in production environments.
• Master or PhD in mathematical fields.
• Strong programming in Python and/or R with MLOps experience.
• Experience with feature engineering on demand data (pricing, promotions, events, weather).
• Experience with RELEX or similar planning systems.

Responsibilities

• Develop promotion of quantity estimation methodologies and tooling for faster planning tasks.
• Drive data-driven decision making by empowering store and demand planning with advanced analysis.
• Establish KPI and reporting framework to enable learning from campaigns and operations.
• Lead ML/AI initiatives in RELEX and integrate large data/AI use cases.
• Coach analysts and specialists across supply chain planning.

Skills

Applied ML

Python

R

MLOps

Feature engineering

Stakeholder communication

RELEX

Education

Master's degree in mathematics

PhD in mathematical fields

Tools

RELEX

Job description

Coop Danmark in Albertslund is seeking a Senior Data Scientist for the new Store Partnering team. You will establish a data-driven approach to Coop’s supply chain, turning data into actionable forecasting and planning insights to improve consumer availability across millions daily.

You will lead development of analytics tools, drive ML/AI initiatives in RELEX, and coach analysts, while enabling a data-centric culture across the planning teams.