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About the Role
As a Lead Data Scientist, you will be a domain expert responsible for the end-to-end design, development, and productionization of machine learning solutions for credit and portfolio management. This senior technical leadership role requires a deep understanding of the business to address pressing challenges and directly impact Billie's P&L. You will own Billie's credit risk modeling domain, collaborate with Engineering, Product, and Data Science peers, and shape the roadmap for ML models and applied AI.
Responsibilities
- Take ownership over key KPIs impacting Billie’s success and P&L.
- Drive the technical solution and execution of high-quality ML solutions across multiple domains.
- Apply advanced AI methodologies (e.g., LLMs, RAG, AI agents, foundation models) to enhance credit scoring capabilities.
- Build state-of-the-art credit risk models (PD, LGD, EAD) and optimize the real-time decision engine.
- Define and execute analytics for complex, cross-domain problems, including hypothesis development and A/B testing.
- Partner with Engineering, Product, and Data Science teams to enhance the decision engine and integrate new data sources.
- Mentor and grow junior Data Scientists.
- Contribute a technical perspective to system design discussions, ensuring credit risk solutions are built for scale.
Requirements
- 6+ years of Data Science experience with significant exposure to the credit domain and deep expertise in PD modeling.
- Broader experience with LGD, EAD, limit policies, and portfolio management is strongly preferred.
- Hands-on proficiency in Python (pandas, scikit-learn, XGBoost, PyTorch/TensorFlow) and SQL (Snowflake, BigQuery).
- Experience with data visualization tools like Tableau.
- Hands-on experience working with LLMs and generative AI, including evaluation, integration, and fine-tuning.
- Proven experience leading the deployment and productionization of ML services.
- Deep understanding of modern MLOps concepts (e.g., containerization, event-driven architectures, model monitoring).
- Hands-on experience with graph databases (e.g., Neo4j) is highly desired.
- Strong business acumen and ability to translate complex business problems into analytical requirements.
- Excellent communication and data storytelling skills.
- Strong product mindset, comfortable owning a roadmap and driving initiatives with minimal direction.
Skills
- Data Science
- Credit Domain Expertise
- PD Modeling
- LGD Modeling
- EAD Modeling
- Scorecard Development
- Model Validation
- Production Monitoring
- Limit Policies
- Portfolio Management
- Python
- pandas
- scikit-learn
- XGBoost
- PyTorch
- TensorFlow
- SQL
- Snowflake
- BigQuery
- Tableau
- LLMs
- Generative AI
- MLOps
- Containerization
- Docker
- Kubernetes
- Event-driven Architectures
- Model Monitoring
- Graph Databases
- Neo4j
- Business Acumen
- Data Storytelling
- Product Mindset
Location
- Berlin
Work Type
- Hybrid
Experience Level
- Lead
- Senior
Benefits
- Challenging and impactful work
- Virtual Shares Incentive Program
- Flexible work hours
- Hybrid working approach (up to 3 days remote)
- 30 days vacation per year
- Sabbatical opportunities
- Extra child sickness leave
- Discounted public transport access
- Yearly development budget
- Free German group classes
- Company and team events
- Interest groups
- Billie run club
- Game nights
About the Company
- Billie is a leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses.
- We offer B2B companies innovative digital payment services and modern checkout solutions.
- Our mission is to create a new standard for business payments and simplify the purchasing experience.
- Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes, and a highly scalable tech platform.
- We are a deep-tech company building financial products.
- We focus on building simple, elegant solutions with automation and scalability.
Equal Opportunity
- Billie is an equal opportunity employer and does 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.
- All qualified applicants are welcome and we especially encourage you to apply, even if you don't check every box in the job description.