Data Scientist (Fintech)

TL;DR

Data Scientist (Fintech): Developing proprietary credit risk models for underwriting and pricing of loan and credit card products with an accent on machine learning techniques and behavioral modeling. Focus on enhancing underwriting quality for the US unsecured loans and credit cards business.

Location: Hybrid in London (Remote Mondays and Fridays, in-office Tuesday to Thursday)

Company

A profitable fintech unicorn dedicated to rebuilding consumer finance products for the UK and US markets.

What you will do

• Develop proprietary behavioral models to inform market-facing underwriting and pricing decisions.
• Translate complex business problems into data-driven questions and implement technical solutions.
• Handle the full ML lifecycle, including self-serving deployment and monitoring of models.
• Design, implement, and evaluate experiments to drive constant product innovation.
• Collaborate in a multidisciplinary capacity across the business to identify and solve risk management issues.

Requirements

• Experience using Python and SQL.
• Strong proficiency in data manipulation with packages such as NumPy and Pandas.
• Deep knowledge of machine learning techniques and their respective trade-offs.
• Ability to communicate results effectively to stakeholders through verbal and written channels.
• Location: Must be based in London to support the hybrid office schedule.

Nice to have

• Prior experience in credit risk for consumer lending or credit cards, particularly for the US market.
• Interest in machine learning engineering and data engineering.

Culture & Benefits

• Hybrid work flexibility with remote Mondays and Fridays.
• Best-in-class compensation package including equity.
• Fresh, healthy lunches prepared by in-house chefs in the office (Tue-Thu).
• Private health insurance coverage.
• Inclusive and open workspace environment.

Hiring process

• Initial screening call with Talent Acquisition.
• Technical take-home task.
• Task debrief and case study interview.
• Final interviews with the leadership team.