Data Scientist - US Products (Fintech)

TL;DR

Data Scientist - US Products (Fintech): Developing proprietary credit risk models for US unsecured loans and credit cards using machine learning techniques with an accent on underwriting, pricing, and risk management. Focus on designing, implementing, and evaluating models, analyzing data from various sources, and deploying solutions for constant innovation.

Location: Hybrid in London, UK (work from home every Monday and Friday, office Tuesday-Thursday)

Company

Fintech unicorn founded in 2014, profitable since 2017, building technology for consumer credit products like loans, credit cards, and car finance in UK and US markets.

What you will do

• Develop and optimize behavioral credit risk models using state-of-the-art ML techniques and rich data sources for underwriting and pricing.
• Translate business problems into data questions, analyze data, and propose solutions across multidisciplinary teams.
• Design, implement, manage, and evaluate experiments for products and services to drive innovation.
• Learn the domain of US unsecured loans and credit cards, focusing on data that informs strategy and risk modeling.
• Communicate results clearly to stakeholders and share ideas with the team.

Requirements

• Experience using Python and SQL.
• Strong proficiency with data manipulation using NumPy, Pandas.
• Knowledge of machine learning techniques and their pros/cons.
• Confident communicator who contributes effectively in a team.
• Self-driven and willing to lead projects or new initiatives.

Nice to have

• Prior experience in credit risk for consumer lending or credit cards, especially US market.
• Interest in machine learning engineering.
• Strong SQL and interest in data engineering.

Culture & Benefits

• Hybrid work: remote Mondays and Fridays, office Tuesdays-Thursdays with in-house chefs providing fresh lunches.
• Best-in-class compensation including equity.
• Private health insurance coverage.
• Equal opportunity employer focused on inclusivity.
• Opportunity to scale a successful fintech company with top Glassdoor and Trustpilot reviews.

Hiring process

• Initial call with TA.
• Take-home task.
• Task debrief and case study interview.
• Final interviews with leadership team.