Data Scientist

About the role

As a Senior Data Scientist for Fraud Prevention, you will design and build robust machine learning solutions to prevent fraud within Billie's B2B payment platform. You'll own the end-to-end modeling lifecycle and work closely with cross-functional teams to deploy models that detect complex debtor behavioral patterns and emerging fraud trends.

What you'll do

• Design and execute high impact anti-fraud solutions, taking full ownership of project priorities and delivering production-ready models
• Apply quantitative analysis, data mining, and advanced ML to model debtor behavioral patterns and identify risk factors
• Collaborate with cross-functional teams to improve decision engine logic, integrate new data sources, and enhance system functionalities
• Own deployment and operationalization of ML services, working with Engineering to define infrastructure requirements
• Act as technical mentor to junior team members and foster culture of technical excellence
• Present technical findings through data storytelling and provide actionable recommendations to stakeholders

What you'll need

• 3-5+ years of experience in data-driven, quantitative, or machine learning roles, preferably in fintech or high-transaction environments
• Direct experience in fraud prevention, risk modeling, or high-transaction fintech environment highly preferred
• Advanced proficiency in Python (pandas, scikit-learn, xgboost) and SQL (Snowflake, Postgres, or MySQL)
• Deep technical expertise in classification models, anomaly detection algorithms, and graph-based networks
• Hands-on experience productionizing ML services with MLOps concepts like containerization and event-driven architectures
• Proven ability to manage stakeholders across technical and non-technical functions
• Strong problem-solving capabilities and ability to translate business challenges into technical requirements
• Strong communication skills with track record of using data to influence organizational strategy

Nice to have

• Experience with data visualization tools like Tableau
• Experience with ML orchestration frameworks such as Metaflow, Apache Flink, or similar MLOps tooling

What they offer

• Virtual shares incentive program
• Hybrid working approach with up to 3 days per week from home
• 30 days vacation per year, sabbatical opportunities, and extra child sickness leave
• Discounted access to Berlin Public Transport, Deutschland-Ticket, or JobRad
• Yearly development budget for skill development
• Free German group classes and multicultural team environment