checkout.com - Data Scientist

London, United Kingdom, Hybrid3mo ago

In Office Mid EMEA Fintech Payments Data Scientist Recruiter Docker Checkout.com AWS GCP Databricks

Requirements

• Experience with advanced data transformation techniques (e.g., lambda functions). • Familiarity with, or hands-on experience in, recommender systems, contextual bandits, or network intelligence applications. • Experience in fintech, payments, or building cross-disciplinary relationships for advice and guidance. • Familiarity with the unix shell, Databricks, Docker, and common cloud platforms (GCP/AWS). • It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. • Life at Checkout.com http://Checkout.com • We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. • Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. • For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

Responsibilities

• Contribute to the research and development of new ML models and estimators to boost core Acceptance Rate performance. • Design and implement experiments to produce actionable insights, focusing on managing time-based data leakage and ensuring robust model evaluation. • Collaborate with other Data Scientists and engineers to productionise ML features, models and evolve our evaluation and monitoring frameworks. • Write high-quality, interpretable Python code for feature engineering and model training, contributing directly to our core products. • Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical and non-technical audiences.