About the role
Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits at the heart of this USP, developing the credit risk models to underwrite loan and credit card products.
You will have access to the latest machine learning techniques combined with a rich data repository to deliver best in market risk models.
Our team's objectives
The data science team develops proprietary risk models which are core to the company’s success.
We work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.
We self-serve with all deployment and monitoring, without a separate machine-learning-engineering team.
How you'll impact these objectives
Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling is essential to being able to successfully contribute value.
Rigorously search for the best models that enhance underwriting quality..
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.
What we're looking for
Experience using Python
Knowledge of the credit industry, including the products, data, typical ML applications
Knowledge of machine learning techniques and their respective pros and cons.
Confident communicator and contributes effectively within a team environment
Self driven and willing to lead on projects / new initiatives
Nice to have's
Interest in machine learning engineering
Strong SQL and interest in data engineering
We’re not corporate, so we try our best to get things moving as quickly as possible. For this role we’d expect:
Initial call with TA
Take home task
Task debrief interview
Case study interview
Final interviews;
Meet the team you’ll work with daily
Meet Head of Data Science and Chief Risk Officer