Senior Data Scientist (m/f/d)

Freshflow GmbH; Berlin; Hybrid; EUR 90.000 - 120.000; Vollzeit

Benefits dieser Stelle

Equity VSOP

Hybrid work Berlin

Relocation support

Fast interview process

Zusammenfassung

Freshflow GmbH is building the AI operating system for the fresh food supply chain, starting with ordering and inventory optimisation for fresh departments. You will join a senior Data Science team tackling the hardest forecasting problems in retail, delivering production-quality models and tools.

The role focuses on distributional forecasting, inventory simulation, and ordering policies, with close collaboration to Customer Success and Engineering.

Qualifikationen

• MSc or PhD in a quantitative field; depth of technical thinking matters more than discipline.
• Strong Python and SQL on large, real-world data; production-grade code.
• Experience with GCP (BigQuery, Cloud Run, Vertex AI) and dbt as part of a modern data stack.
• Familiarity with workflow orchestration (Airflow) and software engineering practices including Git, containerisation and CI/CD.
• Daily fluency with agentic AI coding tools (Claude Code, Cursor or similar).
• Able to translate complex mathematical reasoning into decisions that product teams can act on.

Aufgaben

• Develop and improve distributional forecasting models across architecture, calibration, and coverage; monitor forecast quality.
• Contribute to inventory simulation and ordering-policy framework; drive progress to production.
• Shape technical direction and enforce code quality, testability, and production readiness.
• Improve end-to-end pipeline quality from input data integrity to forecast output and order recommendations.
• Ship production-grade code; stay at the forefront of AI tooling to work efficiently without sacrificing craftsmanship.
• Collaborate with Customer Success and Engineering to translate store-level findings into product improvements.

Kenntnisse

Python

SQL

Forecasting

Machine Learning

GCP

Airflow

Production-grade code

Ausbildung

MSc/PhD in quantitative field

Tools

BigQuery

Vertex AI

dbt

Cloud Run

Git

CI/CD

Jobbeschreibung

Type Full-time Location Berlin · Hybrid, in office Team Data Science

About Freshflow

Today, more than 40% of all food produced globally is wasted, causing $1.2 trillion in losses every year and carbon emissions six times higher than the entire aviation industry. Freshflow is building the AI operating system for the fresh food supply chain, starting with ordering and inventory optimisation for fresh departments.

We already work with some of the largest grocery retailers in Germany and France (EDEKA, REWE, Carrefour, Intermarché, E.Leclerc), meaningfully reducing food waste while improving on-shelf availability. 93% of our order proposals are accepted by store staff. We are growing revenue 400% year over year and just closed our $10M Series A.

You would join a small, senior, dedicated Data Science team, and bring your best work to the hardest forecasting problem in retail and develop cutting edge technology.

The hard and interesting problem you'll work on

Fresh is the hardest and most interesting forecasting problem in retail for several reasons. Products decay on the shelf with uncertain, item-specific shelf lives. The same onion arrives under different item IDs depending on supplier and week, and when a customer buys an apple, the transaction often doesn't record the variety. Turning that into a coherent demand signal is a challenge in itself, before any forecasting begins. On top of that, inventory records are rarely accurate: shrinkage, unrecorded waste, and scanning errors mean the system often doesn't know what's actually on the shelf. Every order is a daily tradeoff between waste and availability, and getting it wrong in either direction has immediate, visible impact in the store.

What you'll do

• Develop and improve our distributional forecasting models, working across model architecture, calibration, and coverage. This includes deepening existing production models, consistently monitoring forecast quality metrics, and acting swiftly when performance degrades as well as identifying where current approaches break and what comes next.
• Make meaningful contributions to our inventory simulation and ordering policy framework, actively driving progress on both and seeing improvements through to production.
• Shape technical direction in your focus area, contributing to methodology decisions and holding a high bar for code quality, testability and production readiness across the team.
• Contribute to end-to-end pipeline quality, from input data integrity through forecast output to live order recommendation performance. This means ongoing monitoring, regular backtesting evaluations to assess model impact, and a shared commitment to catching issues before they reach the store.
• Ship production-quality work, writing well-tested, readable, thoroughly reviewed code. Stay at the forefront of agentic AI tooling (Claude Code, Cursor or similar) and use it to work efficiently without compromising on craft.
• Collaborate closely with Customer Success and Engineering to translate store-level operational findings into product improvements.

Qualifications

• You have built systems that make decisions under uncertainty with real operational consequences, not just research prototypes. Your background is in at least one of probabilistic forecasting, stochastic inventory simulation, or operations research, with solid working knowledge across the others.
• Right now the biggest opportunities are in inventory simulation and ordering-policy design, so depth there will let you make your mark fastest — but if your strength lies elsewhere in this space, we still want to hear from you.
• MSc or PhD in a quantitative field — Statistics, Mathematics, Physics, Operations Research, Computer Science, or similar. What matters most is depth of technical thinking, not the specific discipline.
• Strong Python and SQL on large, messy, real-world data — production-grade code.
• Deep familiarity with distributional and probabilistic forecasting methods (e.g. quantile regression, LGBM with distributional output, GAMLSS-type models, conformal prediction).
• Solid grounding in stochastic inventory theory, newsvendor models, and related policies, service level optimisation.
• Experience with ML model evaluation and monitoring in production settings.
• Comfortable working with GCP (BigQuery, Cloud Run, Vertex AI) and dbt as part of a modern data stack.
• Familiarity with workflow orchestration (e.g. Cloud Composer, Airflow) and software engineering practices including Git, containerisation and CI/CD.
• Daily fluency with agentic AI coding tools (Claude Code, Cursor or similar) — this is how we work.
• Able to translate complex mathematical reasoning into decisions that product teams, Customer Success, and store operators can act on.

Beneficial

• Experience in supply chain optimisation, demand planning, or perishables — grocery retail domain knowledge is a strong plus.
• German or French — the languages our customers operate in.
• Previous startup or scale-up experience.

What we offer

• Equity participation (VSOP).
• Hybrid, based in our Berlin office.
• We support relocation to Berlin.
• A fast, transparent hiring process — screening call, then a case study & interviews, then an offer — typically 2–3 weeks start to finish.

Freshflow is proud to be an equal opportunity employer. This means that we don't discriminate based on race or ethnic origin, color, the language(s) you speak, where you (or your parents) are from, whether or not you consider yourself to have a disability, your age, gender, gender identity, sex, sexual orientation, religion, beliefs, or political opinions. We're a diverse team in many ways, and we love it that way.