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Lendable is a UK unicorn fintech company (700+ employees, profitable since 2017, backed by Balderton Capital and Goldman Sachs) rebuilding consumer finance products—loans, credit cards, and car finance—with best-in-class technology. The company operates in the UK and US markets, delivering credit decisions in minutes instead of days.
You will join the UK Loans team within the Data Science and Analytics function, which sits at the heart of Lendable's real rate risk-based pricing strategy. This team develops credit risk models and pricing strategies to underwrite loan and credit card products, using machine learning and new data sources to continuously improve offerings.
In this role, you will work on projects related to pricing, funnel optimization, and credit strategy in collaboration with credit and product teams. You will be mentored to solve complex analytical problems and will eventually take ownership of your own models. Key responsibilities include:
- Learning the domain of Lendable's products and understanding the data that informs strategy and modeling
- Researching and proposing improvements to existing pricing strategies and modeling methodology
- Working closely with the credit team to align pricing decisions with credit risk and underwriting strategy
- Clearly communicating results to stakeholders through verbal and written communication
- Contributing ideas to the wider team and building collective knowledge
You will work in a small, high-impact team of exceptional people who are resourceful problem-solvers. The role offers the opportunity to take ownership of specific analyses and models while being supported by experienced teammates who will help develop your technical expertise and domain knowledge.
Lendable offers hybrid working (three days in-office weekly at London location), flexible benefits tailored to role and location, private health coverage, retirement savings plans, employee referral bonuses, complimentary lunches on in-office days, and sustainable commuting schemes.
REQUIREMENTS:
- 1–2 years' experience in a technical, analytical, or data-focused role
- Proficiency in Python (pandas, numpy, scikit-learn) and SQL
- Theoretical understanding of core machine learning techniques and statistical principles
- Strong numerical and analytical skills; comfortable working with large datasets
- Confident communicator; effective team contributor
- Self-driven; willing to take ownership of specific tasks and analyses
NICE TO HAVE:
- Exposure to credit risk or financial datasets
- Interest in Data Engineering
- Prior experience with financial or pricing modeling
