Senior Credit Risk Manager
Listed on 2026-01-12
-
Finance & Banking
Data Scientist -
IT/Tech
Data Science Manager, Data Analyst, Data Scientist
About Lendable
Lendable is on a mission to build the world's best technology to help people get credit and save money.
We're building one of the world’s leading fintech companies and are off to a strong start:
One of the UK’s newest unicorns with a team of just over 600 people
Among the fastest-growing tech companies in the UK
Profitable since 2017
Backed by top investors including Balderton Capital and Goldman Sachs
Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)
So far, we’ve rebuilt the Big Three consumer finance products from scratch:
loans, credit cards and car finance
. We get money into our customers’ hands in minutes instead of days.
We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.
Join us if you want toTake ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1
Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo
Build the best technology in-house
, using new data sources, machine learning and AI to make machines do the heavy lifting
We’re looking for a highly analytical, technically strong Senior Credit Manager to join our U.S. team.
In this role, you will help drive a step-change in how we measure, test and understand the performance of our U.S. loans business. You’ll work horizontally across Credit, Data Science, Product, Engineering and Capital Markets to ensure we are making statistically sound, customer-friendly and commercially intelligent decisions.
This is a high-impact, high-autonomy role
. You will own core analytical infrastructure that underpins how we improve credit strategy, evaluate tradeoffs, and scale profitably. The role is ideal for someone who thrives in ambiguity, is comfortable going deep into technical detail, and can translate rigorous analysis into decisions that move the business.
1) Own our Testing Ecosystem (Experimentation + Statistical Rigor)
Own the end-to-end testing ecosystem for credit and product decisions including experimentation design, implementation standards, and result interpretation
Ensure we are collecting the right data
, in the right structure, to answer high-priority questionsEstablish statistically sound testing practices across teams
Develop repeatable frameworks for evaluating tradeoffs between conversion, risk, yield, and customer outcomes
Partner with Product/Engineering to ensure experimentation tools and logging support robust measurement (not fragile analyses after the fact)
2) Build Best-in-Class Monitoring & Analytics Suite (Performance + Economics)
Build and own a cohesive monitoring and analytics suite that provides a nuanced, end-to-end view of the business
Ensure we have clear visibility into credit performance, unit economics, funnel & underwriting performance
Develop tooling that lets us diagnose issues early and confidently
Create a “single source of truth” performance narrative that can be relied on by senior leadership for decision making
3) Drive Portfolio Valuation & Forecasting (Decision Support Across the Business)
Help build and continuously improve our approach to portfolio valuation, performance forecasting, and expectation-setting
Produce credible valuations / forward-looking performance views that inform:
Credit strategy and policy changes
Capital markets funding conversations
Growth scaling decisions
Product prioritisation and roadmap tradeoffs
Ensure valuation approaches are grounded in high-quality assumptions, are transparent, and are calibrated to observed performance Build clear frameworks for answering: what is the portfolio worth, how does it change under different strategy choices, and where are we taking risk?
4) Be Hands-On With Data & Influence Decision Making
Be comfortable being hands-on with data
: drive your own analysis, build models/tools where needed, and turn analysis into crisp recommendations…
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