About Billie
Billie is the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. The company's mission is to simplify the purchasing experience for all businesses and create a new standard for business payments. Billie's solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes, and a highly scalable tech platform, making it a deep-tech company building financial products.
Responsibilities
- Drive the technical solution and execution of high-quality, impactful ML solutions across multiple domains within the Decision Science team
- 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
- 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 to enhance and optimize the decision engine
- Ensure the successful deployment and operationalisation of ML services, collaborating closely with Engineering on service integration
Requirements
- 4+ 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/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) and the ability to rapidly apply this expertise across different business domains
- Proven experience leading the deployment and productionizing of ML services, demonstrating a deep understanding of modern MLOps concepts
- 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
- Excellent communication and data storytelling skills, with a track record of maximizing the impact of technical findings
Benefits
- 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
- Hybrid working approach with up to 3 days per week remote
- 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 to broaden your skill set
- Free German group classes
- Multicultural team with more than 40 nationalities
- Company and team events, interest groups, run club, game nights, and more