Delivery Hero, the Berlin-based local delivery platform active in around 65 countries and listed in the MDAX, is hiring a Senior Data Scientist for its Fintech Data Science team. You will own credit and fraud risk models end to end, from the first question to a live real-time decision engine, with hybrid work, 27 vacation days and an employee share purchase plan.
About Delivery Hero
Business: Local delivery platform operating in around 65 countries
Base: Headquartered in Berlin, listed on the Frankfurt Stock Exchange since 2017 (MDAX)
Team: Fintech Data Science, covering underwriting, portfolio risk and fraud prevention
Way of Working: Daily use of coding agents and LLM tools, with outputs checked
Benefits & Career Opportunity
Work Model: Hybrid, 2 days a week on the Berlin campus
Time Off: 27 vacation days, plus an extra day in the 2nd and 3rd year of service
Learning: 1,000 euro education budget, language courses and Udemy Business
Money: Employee share purchase plan, sabbatical bank, transport discount, corporate pension, life and accident insurance, meal vouchers
Position Overview
As Senior Data Scientist, you own credit and fraud risk problems end to end: framing an unclear question, building and validating the model, getting it live in a real-time decision engine and defending it in front of a risk committee. You build and ship models for fraud and anomaly detection, transaction decisioning, acquisition scorecards and behavioural limit management. You give Risk, Compliance, Finance, Payments and leadership clear, actionable recommendations, work with Engineering on reliability and deployment, build data marts and pipelines for features and training data, and run experiments through to rollout, monitoring and drift fixes.
Why This Role Matters: Your models decide who gets credit and which transactions are stopped, for millions of customers and merchants. For a data scientist who wants real ownership and production impact, this role covers the whole lifecycle, in a team that uses AI tools daily and checks their output.
Key Responsibilities
Models
- Build and ship fraud and anomaly detection, real-time transaction decisioning, acquisition scorecards and behavioural limit management
- Own problems from an unclear business question through data, modelling, deployment, monitoring and adoption
Data & Engineering
- Build data marts and pipelines that produce features and training datasets
- Work closely with Engineering on reliability and own the full data science lifecycle, including deployment
Experiments & Advice
- Drive experiments through to model rollout, then monitor and fix drift at the source
- Give Risk, Compliance, Finance, Payments and leadership a clear recommendation and the reasoning behind it
Qualifications
Experience
- A track record of owning models end to end, from an unclear business question to real use by the business
- Full-stack breadth: SQL and analysis (e.g. BigQuery), orchestration (e.g. Airflow), modelling, deployment (e.g. Metaflow, Vertex AI) and production monitoring
- Strong Python, testing and CI/CD
AI & Judgment
- Fluency with AI tooling: coding agents and LLMs every day, sensible LLM budget use and checking outputs for errors
- Independence and speed, and defensible recommendations under ambiguity, e.g. false positives versus fraud caught
Nice to Have
- Fraud, credit risk, payments or fintech experience
- Real-time or streaming decision systems
- Deep learning or LLM- and agent-based solutions in production
- Clear communication with non-technical stakeholders
About Delivery Hero
Delivery Hero is a local delivery platform operating in around 65 countries, headquartered in Berlin and listed on the Frankfurt Stock Exchange since 2017 as part of the MDAX. It describes a culture that mixes high performance and community, and it welcomes applicants regardless of background.
How to Apply: Apply through the Delivery Hero careers page. Accessibility support can be requested from the Inclusion Officer at inclusion@deliveryhero.com. The posting gives no other contact and no salary figure.
Who Should Apply?
- Senior Data Scientists: With risk or fraud models
- ML Engineers: Wanting end-to-end ownership
- Fintech Analysts: With credit scoring experience
- Real-Time ML Builders: With deployment skills
- Berlin Tech Talent: Seeking hybrid work and a share plan
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