Senior Data Scientist

At Lenkie, we're on a mission to help small businesses turn their bold ambitions into reality. Our lending products make access to capital faster, fairer, and more flexible, enabling SMEs to grow with confidence. We’ve provided millions in funding to hundreds of UK businesses with our loan book growing 4x in 2025 and we’re just getting started.

We are a friendly and collaborative team with a fast-paced and high-performing culture. We are headquartered in London but with team members across Nigeria, South Africa and London. We’re backed by top-tier investors and have recently closed a £49M equity and debt Series A investment round to significantly scale the business across the UK in 2026.

We're looking for a (Senior) Data Scientist with deep credit risk experience to join us as one of our earliest data hires. You'll work closely with the Head of Credit, Credit Risk Manager and CTO to build our modelling capability from the ground up — from scorecard development and underwriting automation to portfolio analytics and early warning systems as well as Customer Lifetime Values.

This isn't a role where you'll plug into an existing machine. You'll be defining how we do things, building the infrastructure, and helping recruit the team around you as we grow.

• Build credit risk models - application scorecards, behavioural models, propensity models - across our SME lending products
• Create portfolio monitoring dashboards, MI packs, and early warning indicators for the credit and leadership teams
• Work with Open Banking, bureau, and alternative data sources to enrich our credit assessment
• Define data science best practices, tooling, and ways of working as the function grows
• Partner closely with Product, Engineering, and Credit to translate business problems into data solutions
• Support the Head of Credit and Credit Risk Manager on strategic projects — limit setting, pricing, risk appetite calibration
• Use your data science expertise for projects outside of credit risk, e.g. Customer Lifetime Value modeling.

• 2–5 years of experience in data science or quantitative analysis, with a strong focus on credit risk in a fintech or lending environment
• Hands‑on experience building credit scorecards or risk models (application, behavioural, or collections)
• Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, etc.)
• Familiarity with Open Banking data, bureau data (Experian, Equifax, TransUnion), or alternative data sources
• Comfort working in small, fast‑moving teams where you have to be both strategic and hands‑on
• Experience with SME lending is a strong plus (vs. consumer)
• Strong communicator — able to explain model outputs and data insights to non‑technical stakeholders

• Be a founding member of the data team with real ownership and influence
• Competitive salary + meaningful equity
• Hybrid working from our London office
• A mission you can get behind - helping small businesses access the finance they deserve

We’re building a diverse, inclusive and supportive team where everyone can do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and we do not discriminate on the basis of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation. If you require any reasonable adjustments during the recruitment process, please let us know.