Senior Data Scientist, Lendable

• 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

Desirable

• 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
• 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
• 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
• 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

• 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