Senior Data Scientist

We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine‑learning‑supported risk models, fully digitized processes and a highly scalable tech platform.

This makes us a deep‑tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.

As a Senior Data Scientist within the 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 various critical business areas (e.g., fraud prevention, credit risk, portfolio optimization). This role requires a deep understanding of the business and the ability to apply your expertise to the most pressing problems, driving a direct and measurable impact on Billie's key strategic goals.

In more detail, you will:

• Drive the technical solution and execution of high‑quality, impactful ML solutions across multiple domains within the Decision Science team, ensuring project success from conception to production.
• Apply exceptional hands‑on expertise in quantitative analysis, data mining, data science, and advanced ML to model complex business patterns, identify risk factors, and optimize Billie's real‑time decision engine logic for various use cases.
• Define and execute the analytics for complex, cross‑domain problems, including developing hypotheses for experimentation, designing A/B tests, and synthesizing results into actionable insights.
• Serve as a technical leader and subject‑matter expert within cross‑functional teams (Data/Software Engineers, Analysts, Product Managers, Business Leaders) to enhance and optimize the decision engine by improving its logic, integrating new data sources, and enhancing functionalities.
• Ensure the successful deployment and operationalisation of ML services, collaborating closely with Engineering on service integration.

• 6+ years of total 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/Tensor Flow) and SQL (Snowflake, Big Query, etc.), and experience with data visualization tools like Tableau.
• Expertise in applying and product ionizing various advanced ML models (classification, deep learning, anomaly detection, graph networks) and the ability to rapidly apply this expertise across different business domains.
• Proven experience leading the deployment and product ionizing of ML services, demonstrating 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.
• Proven experience developing and deploying data science solutions within the fraud, credit risk, or other relevant fintech/risk domains is highly desired.

• Challenging and impactful work that drives personal and professional growth
• One of the best Virtual Shares Incentive Programs in the market, so that everyone at Billie is invested in our success
• Flexible work hours and trust in your ability to deliver, empowering you to take control of your work‑life balance
• A hybrid working approach that allows you to work…