Staff Data Scientist
LemFi provides international payment products for immigrants, including multi-currency wallets, global money transfers, payment requests, and eSIM connectivity.
About LemFi
LemFi is a financial technology company offering international payment products designed to help immigrants thrive financially. Its services include multi-currency wallets, international money transfers to more than 30 countries, money requests and payment links, and eSIM connectivity. Transfers can be sent to bank accounts, mobile money, and other destinations, typically arriving within minutes.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will set the technical direction for credit data science, build and validate predictive models, productionize decisioning systems, monitor performance and fairness, analyze portfolios, advise senior stakeholders, and mentor analysts and data scientists.
Requirements
- Significant hands-on experience in data science or quantitative decisioning.
- Meaningful experience in consumer credit, lending, fintech, or another risk-heavy environment.
- Strong Python and SQL skills.
- Experience building and evaluating predictive models in production.
- Solid knowledge of credit risk concepts and portfolio metrics.
- Experience deploying machine learning or decisioning systems into live products.
- Track record of achieving measurable commercial or risk outcomes.
- Ability to operate at staff level in ambiguous environments.
- Experience with bureau or alternative data sources is advantageous.
- Familiarity with SHAP, LIME, and model governance is advantageous.
- Experience in a high-growth fintech or startup is advantageous.
Responsibilities
- Own the end-to-end data science strategy for credit decisioning.
- Design, train, validate, and iterate on predictive models.
- Partner with engineers to productionize reliable and scalable models.
- Build monitoring frameworks for performance, drift, fairness, and operational impact.
- Translate business problems into hypotheses, experiments, and decision proposals.
- Analyze repayment patterns, loss drivers, and customer segments.
- Mentor analysts and data scientists on methodology and decision quality.
Benefits
- Hybrid work arrangement
