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About the Role
As a Data Scientist, you will sit at the heart of Lendable's market-leading real rate risk-based pricing strategy. You will develop proprietary credit risk models to underwrite loan and credit card products, primarily focusing on the US market, while leveraging advanced machine learning techniques and a rich data repository.
Responsibilities
- Develop proprietary behavioural models to inform underwriting, pricing, scorecard development, and risk management.
- Identify business issues, translate them into data questions, and propose analytical solutions.
- Manage end-to-end deployment and monitoring of models.
- Design, implement, and evaluate experiments to drive product innovation.
- Learn the domain of products and the data that informs strategy and risk modelling.
- Rigorously research and implement models to enhance underwriting quality.
- Communicate results clearly to stakeholders through verbal and written channels.
- Share knowledge and contribute to the wider team's development.
Requirements
- Experience using Python and SQL.
- Strong proficiency with data manipulation packages such as NumPy and Pandas.
- Knowledge of machine learning techniques and their respective pros and cons.
- Confident communication skills.
- Self-driven with the ability to lead projects and new initiatives.
Skills
- Python
- SQL
- NumPy
- Pandas
- Machine Learning
- Credit Risk Modelling
- Data Manipulation
Location
- UK
- US
Work Type
- Hybrid
- Full-time
Benefits
- Flexible working arrangements
- Private health cover
- Retirement and savings plans
- Employee referral programme
- Complimentary lunches on in-office days
- Fully stocked kitchen
- Cycle-to-work scheme
- Electric vehicle salary sacrifice scheme
About the Company
- Fintech company focused on credit and savings products.
- UK unicorn with over 700 employees.
- Profitable since 2017.
- Backed by Balderton Capital and Goldman Sachs.
- Products include loans, credit cards, and car finance.