Want to know if this job is worth applying to?
Greater London, England, United Kingdom
Hybrid
LemFi (Series B) is building the go-to financial app for the Global South.
Moving to a new country shouldn’t mean starting from zero. That's why our team of 400+ spanning 20+ countries is building a financial ecosystem that helps immigrants stay connected to home, build stability, and create wealth regardless of where they are from or where they live.
What began as fast, affordable remittances is now evolving into a complete platform for multi-currency accounts, payments, credit, and long-term financial growth.
With millions of users across the globe, we process over $1B in monthly transactions to 30+ countries, proving that borders shouldn't limit financial opportunity.
LemFi's Credit function is one of the most consequential bets we are making as a business. We lend to customers the traditional financial system has largely ignored, and getting that right - at scale, responsibly, across multiple markets - demands serious data science. As Staff Data Scientist for Credit, you sit at the centre of that effort: partnering across Credit Risk, Product, Engineering, Analytics, and Commercial to shape how we underwrite, monitor, and grow lending. Your models will run in production. Your recommendations will land in the room where senior leadership decides risk appetite and market expansion.
This is not a research role. It is a high-ownership, high-consequence position for someone who wants their work to show up in portfolio performance, approval quality, and customer outcomes - not just in a notebook. You will set the technical and scientific standard for credit decisioning at LemFi, mentor the data scientists and analysts around you, and help the business grow its credit products responsibly.
Own end-to-end data science strategy for Credit, from underwriting and pricing to collections optimisation and lifecycle decisioning, surfacing the highest-value opportunities and driving them to production.
Design, train, validate, and iterate on predictive models (probability of default, loss estimation, segmentation, fraud interaction) using machine learning and statistical methods calibrated to a regulated, real-world environment.
Work with Data Engineering and Software Engineers to productionise models cleanly: features, decision logic, versioning, and monitoring all reliable and scalable before anything goes live.
Build robust monitoring frameworks covering model performance, drift, fairness, and operational impact - with a high bar for explainability and governance that satisfies both internal and regulatory scrutiny.
Partner with Product and Credit leaders to translate ambiguous business problems into measurable hypotheses, experiment designs, and decision proposals - using AI tooling to move fast without sacrificing rigour.
Lead deep-dive portfolio analyses into repayment patterns, loss drivers, and customer segments, converting findings into concrete recommendations for senior stakeholders.
Act as technical mentor and thought partner to analysts and data scientists, raising the bar on problem framing, methodology, and the quality of decisions the team produces.
Significant hands-on experience in data science or quantitative decisioning, with meaningful time in consumer credit, lending, fintech, or another risk-heavy environment where model quality has direct financial consequence.
Strong fluency in Python and SQL for model development, feature engineering, analysis, and production-grade investigative work.
Deep track record building and evaluating predictive models in production: feature pipelines, validation design, calibration, monitoring, and full lifecycle management.
Solid grounding in credit risk concepts and portfolio metrics - probability of default, loss behaviour, bureau and alternative data - and the practical judgement to apply them in a fast-moving startup.
Experience partnering with engineering teams to deploy decisioning or ML systems into live products, not just offline research environments.
A clear record of turning analytical work into measurable commercial or risk outcomes: improving approval quality, reducing losses, increasing conversion responsibly, or sharpening collections strategy.
Confident operating at staff level in ambiguity: setting direction without fully defined scope, influencing senior stakeholders, and improving systems through judgement.
Experience with bureau data integrations or alternative data sources in emerging or frontier markets.
Familiarity with explainability frameworks (SHAP, LIME) and regulatory expectations around model governance in consumer lending.
Prior experience in a high-growth fintech or startup where you have had to balance scientific rigour with speed of iteration.
Love shouldn’t be expensive, yet those working hardest for their families often face predatory fees and banking exclusion. We're changing this.
At LemFi, you won’t be just a cog in a machine. Whether designing products, scaling operations, or telling our story, you’ll tackle complex challenges with real, immediate impact. Your work goes beyond metrics - it puts money back in families’ pockets and offers access to the previously excluded. Join us to make a meaningful difference, where high performance is a lifeline for millions.
You can connect with us on LinkedIn and Instagram and if you haven't already, download the app on the App Store or Google Play.
