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.
About the role:
As a (Senior) Data Scientist for Fraud Prevention, you will be a key technical pillar within the broader Decision Science group. You will be responsible for designing and building robust, scalable machine learning solutions aimed at preventing fraud. A mission that has a direct and measurable impact on Billie's bottom line. You will own the end-to-end modeling lifecycle, from defining the analytical approach and testing hypotheses to deploying models that understand complex debtor behavioral patterns and emerging fraud trends.
In more detail, you will:
Design and execute high impact anti-fraud solutions, taking full ownership of project priorities and ensuring the delivery of high-quality, production-ready models.
Apply extensive expertise in quantitative analysis, data mining, and advanced ML to model debtor behavioral patterns, identify risk factors, and optimize Billie's real-time decision engine logic.
Collaborate deeply within cross-functional teams of data and software engineers, analysts, and product managers to improve decision engine logic, integrate new data sources, and enhance system functionalities.
Own the deployment and operationalization of ML services, working closely with Engineering to define requirements for robust infrastructure, including containerization and event-driven architectures.
Act as a technical mentor to junior team members, fostering a culture of technical excellence, rigorous experimentation, and best-in-class coding standards.
Maximize the impact of technical findings on critical business decisions through excellent data storytelling and clear, actionable recommendations for stakeholders.
What you bring to the team:
3-5+ years years of experience in a data-driven, quantitative, or machine learning role, ideally within fintech or a high-transaction environment. Direct experience in fraud prevention, risk modeling, or a high-transaction fintech environment is highly preferred.
Advanced proficiency in Python (pandas, scikit-learn, xgboost) and SQL (Snowflake, Postgres, or MySQL), with a strong grasp of data visualization tools like Tableau.
Deep technical expertise in general classification models (classical and deep learning), anomaly detection algorithms, and graph-based networks.
Hands-on experience productionizing ML services, demonstrating a strong understanding of modern MLOps concepts such as containerization (Docker/Kubernetes) and event-driven architectures.
Proven ability to manage stakeholders across both technical and non-technical functions, aligning technical roadmaps with business priorities.
Sharp problem-solving capabilities with the ability to translate complex business challenges into clean, efficient, and scalable technical requirements.
Strong communication skills, with a track record of using data to influence organizational strategy and drive cross-functional engagement.
Experience with ML orchestration frameworks such as Metaflow, Apache Flink, or similar MLOps tooling.
What We Offer:
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 from home for up to 3 days per week
Enjoy 30 days vacation per year, sabbatical opportunities, and extra child sickness leave for parents.
Our “Catch a Ride with Billie” program that enables discounted access to Berlin Public Transport (BVG), Deutschland-Ticket, OR JobRad
A yearly development budget to broaden your skill set and horizons
Free German group classes
An English-speaking, multicultural team with more than 40 nationalities
Building meaningful connections with your colleagues through company and team events, interest groups, the Billie run club, game nights, and more, powered by our Formula Fun Team!
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. All qualified applicants are welcome and we especially encourage you to apply, even if you don't check every box in the job description.
For information about data processing see our "Recruiting Privacy Policy and further information": https://www.billie.io/en/candidate-information
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