About the role
About the team
Lendable is the UK market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science and Analytics sits at the heart of this USP, developing the credit risk models and strategies to underwrite loan and credit card products.
Our team is primarily focused on the pricing domain but we also work on other areas including product and credit. We implement a range of machine learning techniques and analytical tools to continually improve our product offering.
You will be working in the UK Loans team at Lendable and will work on projects related to pricing, funnel and credit optimisation in collaboration with the credit and product teams.
Join us if you want to
Work in a small, high-impact team where you will be mentored to solve complex analytical problems, eventually taking ownership of your own models
Be resourceful to solve problems and find smarter solutions than the status quo.
Work closely with other members of the team that will support developing your technical expertise and domain knowledge
Our team’s objectives
The pricing team owns the loans funnel analytics and pricing strategy.
We work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.
How you’ll impact those objectives
Learn the domain of products that Lendable serves, understanding the data that informs strategy and modelling is essential to being able to successfully contribute value.
Research and propose improvements to our existing strategies and modelling methodology
Clearly communicate results to stakeholders through verbal and written communication.
Share ideas with the wider team, learn from and contribute to the body of knowledge.
Key Skills
Experience using Python (pandas, numpy, scikit-learn) and SQL
Theoretical understanding of core ML techniques and statistical principles
Confident communicator and contributes effectively within a team environment
Self-driven and willing to take ownership of specific tasks and analyses
Nice to Have
Interest in Data Engineering
Exposure to credit risk or financial datasets
Prior experience with financial modelling
The interview process
For this role we’d expect:
A phone call with one of the team
Video Call case study (Remote)
An exercise to complete in your own time
Onsite Interview
Discuss the exercise you completed
Meet the team you’ll work with daily
