Lead Credit Risk Data Scientist, Billie
+ Virtual Shares Incentive Program
2+ days a week in office
Buy Now, Pay Later payments for business
Posted today
Buy Now, Pay Later payments for business
101-200 employees
Posted today
+ Virtual Shares Incentive Program
2+ days a week in office
101-200 employees
Company mission
To simplify purchasing for all companies and open up new opportunities for growth.
Role
Who you are
- This role requires a deep understanding of the business and the ability to apply your expertise to the most pressing challenges, driving a direct and measurable impact on Billie's P&L
- 6+ years of Data Science experience, with significant exposure to the credit domain and deep expertise in PD modeling: from scorecard development and model validation through to production monitoring. 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, etc.), and experience with data visualization tools like Tableau
- Hands-on experience working with LLMs and generative AI, with the ability to evaluate, integrate, and fine-tune models in a production environment
- Proven experience leading the deployment and productionization of ML services, demonstrating a deep understanding of modern MLOps concepts like containerization (e.g., Docker, Kubernetes), event-driven architectures, and model monitoring
- Hands-on experience with graph databases (e.g., Neo4j) to model, analyze, and extract features from highly interconnected data is also highly desired
- 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
- A strong product mindset: you're comfortable owning a roadmap, making trade-offs under uncertainty, and driving initiatives forward with minimal direction, translating business ambition into a clear technical plan
What the job involves
- As a Lead Data Scientist within the Credit Data Science team, you will serve as a domain expert responsible for the end-to-end design, development, and productionization of robust, scalable machine learning solutions for our credit and portfolio management domain
- Reporting directly to the VP of Data Science and based in Berlin, this is a senior technical leadership role; you will own Billie's credit risk modeling domain end-to-end end-to-end, work in close partnership with Engineering, Product, and Data Science peers, and play a central role in shaping and executing on the roadmap for state-of-the-art ML models and applied AI that power our fast-growing business
- Take ownership over one of the most important KPIs leading to Billie’s success, directly impacting our P&L with your expertise
- Drive the technical solution and execution of high-quality, impactful ML solutions across multiple domains within the Data Science team, ensuring project success from conception to production
- Identify and apply advanced AI methodologies to push Billie's credit scoring capabilities beyond conventional approaches, turning emerging techniques into production-ready solutions (e.g. LLMs, RAG, AI agents, foundation models)
- Apply exceptional hands-on expertise in quantitative analysis, data mining, data science, and advanced ML to model complex business patterns, build state-of-the-art credit risk models (PD, LGD, EAD, etc), 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
- Partner closely with Engineering, Product, and Data Science teams to enhance and optimize the decision engine, improving its logic, integrating new data sources, and enhancing functionalities. You will be a key voice in technical discussions across team boundaries, ensuring credit risk thinking is embedded in how Billie builds its systems
- Mentor and grow junior Data Scientists within the team, and bring a technical perspective to system design discussions across backend and ML, ensuring credit risk solutions are built for scale from the ground up
Our take
Buy Now, Pay Later (BNPL) options have exploded in popularity in recent years, with companies such as Klarna and Clearpay providing an additional line of credit to customers, allowing them to split the cost of their purchases over several instalments. Billie is a BNPL built for business transactions, using machine-learning driven risk models to finance B2B purchases responsibly.
With 1 million customers processing more than 3 billion euros on its platform, Billie is relatively unchallenged in its market. While BNPL firms like Afterpay and Klarna could theoretically move into the B2B space, they are specialised in B2C financing and lack Billie's data on the B2B sector. Billie also boasts a range of features designed specifically for intra-company sales, such as instant verification, invoicing tools and business payment options, which give it a significant advantage against any new rivals.
Billie has raised impressive funding from investors, most recently in a 2021 Series C round. Additionally, its 2022 integration with Klarna and its 2025 announced availability on Stripe have removed major roadblocks to its future expansion. These moves, alongside its entrance into more markets in Europe, will likely speed the company's ascension to Unicorn status and solidify its market lead in the BNPL space.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Oct 2021
$100m
SERIES C
Jul 2019
$34.9m
SERIES B
Total funding: $150.7m
Company benefits
- Flexibility first: We come to the office for important events, but do not have a permanent office presence. Our teams decide how to get the best results
- 30 days vacation per year and 5 extra paid days to look after sick children
- Virtual Share Program
- German language courses from different language levels free of charge
- One-off relocation bonus to make your move easier
- Reimbursement of travel expenses and discount on local public transport in Berlin with the BVG
- Individual training budget of 1,000 euros for courses, conferences and more every year
- Free gym access, weekly yoga classes, healthy snacks, cereals, drinks and more
Company HQ
Friedrichshain, Berlin, Germany
Leadership
Aiga Senftleben
(Co-Founder & MD)Previously worked on a Legal Counsel at eBay and Paypal. Also worked at Funding Circle Deutschland as a General Counsel and is now a member of the Digital Finance Forum at the Federal Ministry of Finance (Germany).
Christian Grobe
(Co-Founder & MD)Graduated from the Free University of Berlin with a Ph.D. in Political Science. Previously co-founded Funding Circle/Zencap where they served as the Managing Director. Also Worked as an Engagement Manager at McKinsey & Company.
Dr. Matthias Knecht
(Co-Founder & Co-CEO)Previously co-founded Funding Cirlce/Zencap where they served as Managing Director. Also worked as an Engagement Manager at McKinsey & Company.
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