Product Data Scientist (Fintech)

TL;DR

Product Data Scientist (Fintech): Driving product strategy and performance measurement for a global payment platform with an accent on actionable insights, data modeling, and experimental design. Focus on collaborating with cross-functional teams to define success metrics, optimize product roadmaps, and foster a data-driven culture.

Location: Must be based in London (Hybrid: 3 days per week in office)

Company

Checkout.com is a global fintech company powering digital payments for major brands like Uber Eats, Klarna, and Sony, with a focus on high-performance and scalable payment infrastructure.

What you will do

• Lead analytics for a product pillar by defining, measuring, and presenting key performance metrics.
• Contribute to product roadmaps through data-based recommendations and identify high-impact improvement areas.
• Collaborate with Data Analytics and Software Engineers to ensure robust data collection and modeling.
• Build experiments and analysis frameworks to quantify the ROI of product development.
• Foster a data-driven culture by sharing insights and building strong relationships across the organization.
• Apply and promote best practices in analytics from data collection through to final analysis.

Requirements

• Must be based in London or able to work from the London office 3 days per week.
• Strong analytical mindset with experience converting ambiguous problems into structured, data-informed solutions.
• Excellent data interrogation skills using SQL.
• Solid knowledge of applied statistics, including hypothesis testing and regression.
• Strong communication skills with the ability to explain complex technical topics to non-technical stakeholders.

Culture & Benefits

• Hybrid working model designed to support collaboration and connection.
• Opportunity to work on a career-defining product in the fast-paced fintech sector.
• High-performance environment with a focus on ownership and impact.
• Supportive team structure with access to a wider network of data professionals.
• Commitment to accessibility and inclusive working environments.