Credit Risk - Data Scientist

Human Capital Solutions
E145Re, E14 5RE, United Kingdom
Last week
£65,000 – £75,000 pa
Applications closed

Related Jobs

View all jobs
Spotlight

Data Analytics Lead

Audit Wales Cardiff, United Kingdom
£63,137 – £73,129 pa Hybrid

Credit Risk Modeller

Pontoon Manchester, United Kingdom
£500 ph Hybrid

Associate Credit Risk Consultant

Harnham - Data and Analytics Recruitment London, United Kingdom
£70,000 pa

Seniot Credit Pricing Manager

Harnham - Data and Analytics Recruitment Liverpool, United Kingdom
£75,000 – £89,000 pa

Deployment Strategist, New Grad - Intel, US Government

Palantir Technologies United States
£110,000 – £170,000 pa

Deployment Strategist

Palantir Technologies Australia
Hybrid

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 (Last week)

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.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.