Commercial Data Scientist

Job description

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. About the Role As a Commercial Data Scientist at Checkout.com , you will be the primary operator of our Growth Prediction Engine . Your focus will be to maintain and evolve the models that underpin our commercial strategy, working closely with Strategic Finance and Revenue Operations. The growth forecasting framework is an established roadmap. You will own the execution of these models while working in a shared-delivery model where tasks are distributed across the wider Data Science team. How You’ll Make an Impact Advance our ML-Driven Forecasting: Own, maintain, and continuously enhance our ML-driven revenue growth models. You will be responsible for pushing these models to the next level and proactively expanding their use cases beyond the commercial domain. Drive Strategic Financial Modeling: Partner with Strategic Finance to build robust projections and simulations based on our forecast model outputs, approaching this with the mindset of building scalable, automated tools rather than just ad-hoc reports. Unlock Commercial Data Science Applications: Work closely with the Revenue Operations team to identify, unlock, and deploy other high-impact commercial data science applications that increase the quality and utilization of our data. Champion Best Practices: Lead by example within your team and the broader data community by applying best practices in analytics and machine learning, from data collection to deployment and analysis.…