Product Data Scientist

Company Description We’re Checkout.com . You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. As a Product Data Scientist, you'll work as part of a cross-functional team alongside product managers, designers, and software and analytics engineers, using data and your analytical expertise to influence the strategy of our Activation, Risk and Configuration products. You'll focus on Platforms and SMB domain where you will help optimize the onboarding journey for merchants and scale predictive automation. You'll help define how we measure the success of our products, collaborate with engineers on data collection, build analytical frameworks, and run insights to find product improvement opportunities. Data Analytics at Checkout.com is a highly visible function that critically impacts the company’s success. As part of this group, you'll have a strong support network of Senior Data Scientists, Analytics Engineers, and Data Product Managers to help you develop your technical and data science practice. How You’ll Make an Impact Efficiency & Product Measurement: Build experiments and analysis frameworks to measure the operational efficiency and ROI of new software releases and internal tooling updates for the Platforms & SMB domain. Data Partnerships: Work closely with Data Analytics Engineers and Software Engineers to ensure we log and model the right data to produce high-integrity business insights. Data-driven automations and solutions: Apply statistical modeling and exploratory data analysis to identify bottlenecks and drop-off points across the merchant onboarding journey, delivering insights to help Product Managers prioritize automation initiatives. Design and run proof-of-concept (PoC) machine learning models and heuristic solutions to evaluate the feasibility of proposed onboarding automations before engineering handoff for implementation. What We’re Looking For Experience: Proven experience in similar data science or product analytics roles and in a high-growth tech environment Technical foundations: Excellent data interrogation skills with SQL and the ability to comfortably write, read, and iterate through Python scripts to run data science analyses. Foundational ML knowledge: A good understanding of foundational data science concepts (e.g., statistics, clustering, basic NLP workflows). You do not need experience deploying ML models to production, but you should understand how to apply them to data tasks. Analytical Mindset: A strong analytical mind with a demonstrable ability to take operational problems and convert them into structured, data-informed solutions. Communication: Clear and precise communicator, able to explain data insights and analytical logic to non-technical stakeholders (Product Managers and Operations teams). Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where amb