Billie is hiring a Data Scientist to join our Decision Science group. You will serve as a cross-domain expert responsible for the end-to-end design, development, and productionization of robust, scalable machine learning solutions across critical business areas like credit risk. This role requires applying deep expertise to pressing problems to drive a direct impact on Billie's strategic goals.
What You'll Do
- Drive the technical solution and execution of high-quality, impactful ML solutions across multiple domains, ensuring success from conception to production.
- Apply hands-on expertise in quantitative analysis, data mining, and advanced ML to model complex business patterns, identify risk factors, and optimize our real-time decision engine logic.
- Define and execute analytics for complex, cross-domain problems, including developing hypotheses, designing A/B tests, and synthesizing results into actionable insights.
- Serve as a technical leader and subject matter expert within cross-functional teams to enhance and optimize the decision engine by improving its logic and integrating new data.
- Ensure the successful deployment and operationalisation of ML services, collaborating closely with Engineering on service integration.
What We're Looking For
- 4+ years of experience in a data-driven, quantitative, or machine learning role, with a focus on deep technical execution and demonstrable ML expertise.
- Hands-on proficiency in Python (pandas, scikit-learn, xgboost, PyTorch/TensorFlow) and SQL (Snowflake, BigQuery, etc.), and experience with data visualization tools like Tableau.
- Expertise in applying and productionizing various advanced ML models (classification, deep learning, anomaly detection, graph networks) across different business domains.
- Proven experience leading the deployment and productionizing of ML services, with a deep understanding of modern MLOps concepts like containerization (e.g., Docker, Kubernetes), event-driven architectures, and model monitoring.
- Experience with orchestration frameworks like Metaflow, Kubeflow, Airflow or similar MLOps tools.
- Hands-on experience with graph databases (e.g., Neo4j) to model, analyze, and extract features from highly interconnected data.
- Strong business acumen and the ability to translate complex business problems into clear analytical and technical requirements that deliver maximum value.
- Excellent communication and data storytelling skills, with a track record of maximizing the impact of technical findings on organizational decision-making.
Nice to Have
- Proven experience developing and deploying data science solutions within the fraud, credit risk, or other relevant fintech/risk domains.
Technical Stack
- Python, pandas, scikit-learn, xgboost, PyTorch/TensorFlow
- SQL, Snowflake, BigQuery, Tableau
- Docker, Kubernetes
- Metaflow, Kubeflow, Airflow
- Neo4j
Team & Environment
You will be part of the Decision Science group, working within cross-functional teams including Data/Software Engineers, Analysts, Product Managers, and Business Leaders. We love building simple and elegant solutions and strive for automation and scalability. You’ll build meaningful connections through company and team events, interest groups, run club, game nights, and more.
Benefits & Compensation
- Challenging and impactful work that drives personal and professional growth.
- One of the best Virtual Shares Incentive Programs in the market.
- Flexible work hours and trust in your ability to deliver.
- 30 days vacation per year.
- Sabbatical opportunities.
- Extra child sickness leave for parents.
- “Catch a Ride with Billie” program for discounted access to Berlin Public Transport (BVG), Deutschland-Ticket, OR JobRad.
- A yearly development budget.
- Free German group classes.
- An English-speaking, multicultural team with more than 40 nationalities.
- Company and team events, interest groups, run club, game nights.
Work Mode
This role is based in Berlin and follows a hybrid working approach, allowing you to work from home for up to 3 days per week.
Billie is an equal opportunity employer and we do not discriminate on the basis of race, color, religion, sexual orientation, gender identity or expression, national origin, age, disability, or any other protected characteristic. We are committed to creating an inclusive environment where everyone feels they belong.
