Onsite
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 700 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.
Take 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
About the role
We are excited to be hiring a new Senior Data Scientist to join our Cards Data Science team.
Data Science sits at the heart of Lendable’s competitive advantage. Our proprietary machine learning models power underwriting, pricing, credit strategy and customer management decisions across millions of lending decisions.
This role will focus on our UK credit cards business, working across both acquisitions and customer management. You’ll work with large-scale, high-dimensional datasets to develop models and strategies that directly influence growth, risk and profitability.
The role combines deep quantitative work with product and commercial thinking. Successful candidates are excited by autonomy, solving difficult problems, moving quickly, experimenting rigorously and influencing strategy through data. We value intellectual curiosity and an interest in emerging machine learning techniques and their practical application.
As you grow in the role, there is significant flexibility to shape your trajectory — whether toward advanced modelling and research, commercial optimisation and strategy, or broader technical ownership.
Our team’s objectives
The Data Science team develops proprietary behavioural and underwriting models using state-of-the-art machine learning techniques and a diverse range of data sources.
Data scientists work closely with product, engineering, credit risk and commercial teams to identify opportunities, translate business problems into quantitative frameworks, and deliver solutions that materially improve business performance.
We operate with a high degree of ownership and autonomy. Data scientists are responsible not only for developing models, but also for deploying, monitoring and continuously improving them in production.
We value rigorous thinking, intellectual curiosity and fast execution. Research is important, but practical impact matters equally.
How you’ll impact those objectives
Develop and deploy machine learning models that improve underwriting, pricing and customer management decisions.
Work with large and complex datasets to generate insights that influence credit and commercial strategy.
Take ownership of models and decision systems throughout their lifecycle, from research and development through production monitoring and iteration.
Collaborate with stakeholders across the business to translate ambiguous problems into measurable outcomes.
Contribute to the team’s technical knowledge through idea sharing, experimentation and continuous learning.
Key Skills
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.
Curious, fast-moving and highly collaborative mindset.
Nice to have
Interest in advanced machine learning techniques and applied research.
Experience in credit risk, lending or broader financial services.
Interest in machine learning infrastructure and optimisation.
The interview process
We’re not corporate, so we try our best to get things moving as quickly as possible. For this role, we’d expect:
Recruiter call
Take Home Task
Technical Interview
Case study
Final interview
Winning team: the opportunity to scale up one of the world’s most successful fintech companies
Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites
Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls
Health coverage: support for your physical and mental wellbeing, including private health cover
Retirement & savings: long-term financial wellbeing through retirement savings plans
Employee referral programme: earn a competitive bonus when you refer successful new team members
Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations
Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations
Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.
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