Senior Data Scientist

About the Role

You'll join a small, senior Data Science team tackling one of the hardest forecasting problems in retail: fresh produce ordering. Every decision is a daily tradeoff between waste and availability, with immediate, visible impact in live stores — this is production ML with real operational consequences.

What You'll Do

• Develop and improve distributional forecasting models, working across architecture, calibration, and coverage.

• Monitor forecast quality metrics consistently and act swiftly when performance degrades.

• Contribute meaningfully to inventory simulation and ordering policy frameworks, driving improvements through to production.

• Shape technical direction in your focus area, contributing to methodology decisions and upholding high standards for code quality and production readiness.

• Own end-to-end pipeline quality, from input data integrity through forecast output to live order recommendation performance.

• Conduct ongoing monitoring and regular backtesting evaluations to assess model impact before issues reach stores.

• Ship production-quality, well-tested, readable code with thorough review.

• Leverage agentic AI tooling to work efficiently without compromising on craft.

• Collaborate with Customer Success and Engineering to translate store-level findings into product improvements.

What We're Looking For

• 5+ years building systems that make decisions under uncertainty with real operational consequences — not research prototypes.

• MSc or PhD in a quantitative field (Statistics, Mathematics, Physics, Operations Research, Computer Science, or similar).

• Background in probabilistic forecasting, stochastic inventory simulation, or operations research, with solid working knowledge across all three.

• Deep familiarity with distributional and probabilistic forecasting methods: quantile regression, LGBM with distributional output, GAMLSS-type models, conformal prediction.

• Solid grounding in stochastic inventory theory, newsvendor models, and service level optimisation.

• Production-grade Python and SQL on large, messy, real-world datasets.

• Experience with ML model evaluation, monitoring, and backtesting in production environments.

• Comfortable with GCP (BigQuery, Cloud Run, Vertex AI), dbt, and workflow orchestration (Cloud Composer, Airflow).

• Strong software engineering practices: Git, containerisation, CI/CD.

• Daily fluency with agentic AI coding tools (e.g. Claude Code, Cursor, or similar).

• Fluent in English; German or French is a strong plus.

• Domain knowledge in supply chain optimisation, demand planning, or perishables/grocery retail is a valuable plus.

• Prior startup or scale-up experience is a plus.

Compensation & Benefits

• Salary: €70,000 – €110,000 annually

• Visa sponsorship: available

Location

Hybrid — Berlin, Germany. Relocation support to Berlin is available.