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LemFi is a Series B fintech platform serving the Global South, processing over $1B in monthly transactions across 30+ countries. The company operates a 400+ person team spanning 20+ countries, building a financial ecosystem for immigrants with multi-currency accounts, payments, credit, and wealth-building products.
You will be the senior-most individual contributor for data science within LemFi's Credit function, sitting at the intersection of Credit Risk, Product, Engineering, Analytics, and Commercial teams. This is a high-leverage role with direct influence on lending decisions, portfolio performance, and customer outcomes.
Key responsibilities include:
- Owning end-to-end data science strategy for Credit, identifying high-value opportunities across underwriting, pricing, line assignment, fraud/risk interaction, collections optimization, and lifecycle decisioning
- Designing, training, validating, and iterating on predictive models that improve credit outcomes using statistical thinking, machine learning, and practical judgment in a regulated environment
- Productionizing models cleanly with Data Engineering and software engineers, ensuring features, decision logic, and monitoring are reliable, version-controlled, and scalable
- Translating ambiguous business problems into measurable hypotheses, model frameworks, and experiments in partnership with Product and Credit leadership
- Building robust monitoring frameworks for model performance, drift, fairness, and operational impact with high standards for explainability and governance
- Conducting deep-dive analyses into portfolio behavior, repayment patterns, loss drivers, and customer segments to uncover actionable opportunities
- Mentoring analysts, data scientists, and cross-functional stakeholders, raising the bar on problem framing, methodology, and decision quality
You bring significant experience in data science, machine learning, or quantitative decisioning—ideally with meaningful time in consumer credit, lending, fintech, or risk-heavy environments. You have strong hands-on fluency in Python and SQL, deep experience building and evaluating predictive models in production, and solid grounding in credit risk concepts including probability of default, loss behavior, and segmentation. You've partnered with engineering teams to deploy decisioning systems into live products and have a track record of turning analytical work into measurable commercial or risk outcomes. You operate comfortably at staff level, setting direction in ambiguity, influencing senior stakeholders, and improving systems through judgment. You're scientifically rigorous but pragmatic, credible with both technical and non-technical audiences, and motivated by high-stakes decisioning where accuracy, fairness, and reliability matter.
