Credit Risk - Data Scientist

Human Capital Solutions
E145Re, E14 5RE, United Kingdom
3 weeks ago
£65,000 – £75,000 pa
Applications closed

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Salary

£65,000 – £75,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
Hybrid
Seniority
Mid
Education
Degree
Visa Sponsorship
Available
Posted
30 Jul 2026 (3 weeks ago)

Benefits

25 days holiday + bank holidays Pension scheme Flexible working Professional development support

Data Scientist — Credit Risk & Decisioning | London

An institutionally backed UK fintech lender with big growth ambitions seeks a Data Scientist-Credit Risk to own the analytics behind how it lends. You'll turn application, credit bureau and Open Banking data into the scorecards, policies and pricing that decide who gets lent to, at what price, and how the book performs.

You'll join at an early stage but alongside an experienced team: leadership have built a UK challenger lender and held senior roles at major UK banks. It's a real chance to help shape a lender as it grows.

What you'll do:

  • Build, test and monitor risk policies, scorecards and pricing rules (including affordability and fraud), quantifying impact on approvals, losses and profitability
  • Track portfolio performance through vintage, cohort and early-warning analysis
  • Build reusable analytical pipelines and tooling in Python and SQL
  • Support pricing, affordability and loss-forecasting, and build dashboards for internal stakeholders and funders

What we're looking for:

  • A strong degree (2:1+) in a quantitative discipline (Maths, Stats, Physics, Engineering, CS or quantitative Economics)
  • Python and SQL, plus solid grounding in statistical and ML techniques
  • Experience in credit risk, data science or another quantitative role — we care more about ability than years. Financial services / lending exposure is a plus; bureau and Open Banking familiarity is a bonus, not a must

Genuine ownership from day one, direct access to an experienced leadership team, and the chance to help build a lending business from the ground up.

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