Job Overview
Location
London
Job Type
Full-time
Category
Data Scientist
Date Posted
May 16, 2026
Full Job Description
đź“‹ Description
- • Develop and deploy proprietary machine learning models to improve underwriting, pricing, and customer management decisions for Lendable’s UK credit cards business.
- • Work with large-scale, high-dimensional datasets to generate actionable insights that directly influence credit strategy, risk assessment, and commercial growth.
- • Own the full lifecycle of machine learning models—from research and development to production deployment, monitoring, and iterative improvement.
- • Collaborate closely with product, engineering, credit risk, and commercial teams to translate ambiguous business problems into measurable quantitative frameworks.
- • Build models leveraging state-of-the-art machine learning techniques and diverse data sources to enhance lending decisions across millions of customer interactions.
- • Apply statistical and quantitative methods to solve complex problems in credit risk and customer behavior analysis within a fast-paced fintech environment.
- • Drive experimentation and rigorous testing to validate model performance and ensure alignment with business KPIs around growth, profitability, and risk.
- • Contribute to the team’s technical knowledge through active idea sharing, research exploration, and continuous learning on emerging machine learning applications.
- • Influence strategic decision-making by communicating data-driven recommendations to non-technical stakeholders across the organization.
- • Work autonomously within a small, high-performing team to identify opportunities for innovation and deliver solutions that outperform traditional financial industry practices.
- • Engage with real-time and historical behavioral data to optimize acquisition strategies and enhance customer retention and lifetime value.
- • Maintain a strong focus on practical impact, ensuring models are not only technically sound but also operationally scalable and commercially viable.
- • Participate in cross-functional initiatives to integrate machine learning outputs into production systems and decision pipelines used by credit and operations teams.
- • Stay up-to-date with advancements in applied machine learning and explore innovative techniques that can be practically implemented within Lendable’s lending ecosystem.
- • Ensure model transparency, fairness, and regulatory compliance in alignment with UK financial services standards and internal governance protocols.
🎯 Requirements
- • Strong programming skills in Python and SQL
- • Understanding of statistics, machine learning, and quantitative problem solving
- • Ability to approach ambiguous problems with structure and pragmatism
🏖️ Benefits
- • Flexible working: hybrid roles require three days in-office weekly; fully remote roles include regular in-person socials and off-sites
- • Private health cover for physical and mental wellbeing
- • Retirement & savings plans to support long-term financial wellbeing
- • Complimentary lunches prepared by in-house chefs on in-office days at select locations
- • Cycle-to-work and electric vehicle salary sacrifice schemes available in select locations
- • Employee referral programme with competitive bonus payouts
Skills & Technologies
About Lendable Ltd
Lendable is a UK-based fintech that operates an online consumer-lending platform using open-banking data and machine-learning underwriting to offer unsecured personal loans and car finance. Founded in 2014 and headquartered in London, it funds loans through an institutional peer-to-peer model, matching investors with borrowers seeking fast, fixed-rate credit. The company automates identity, affordability and risk assessment, providing near-instant decisions and same-day payouts while giving investors access to diversified consumer credit returns. Regulated by the Financial Conduct Authority, Lendable has originated more than ÂŁ2 billion in loans without maintaining physical branches, focusing on transparent pricing and mobile-first customer experience.
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