Data Scientist

Salary: £45,000 - 83,000 per year

Requirements:

• 3+ years of experience developing machine learning models to solve business problems.
• Strong understanding of supervised machine learning algorithms, tuning, and performance evaluation.
• Experience with a range of feature engineering techniques, including target encoding.
• Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation.
• Experience writing clean, production-grade Python code for both model training and inference.
• Excitement to leverage LLMs for coding support and process optimisation to maximise personal and team productivity.
• Experience with advanced data transformation techniques, such as lambda functions, is nice to have.
• Familiarity with, or hands-on experience in, recommender systems, contextual bandits, or network intelligence applications is nice to have.
• Experience in fintech, payments, or building cross-disciplinary relationships for advice and guidance is nice to have.
• Familiarity with the unix shell, Databricks, Docker, and common cloud platforms such as GCP or AWS is nice to have.

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, with a focus on managing time-based data leakage and ensuring robust model evaluation.
• Collaborate with other Data Scientists and engineers to productionise ML features and 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.

Technologies:

• AWS
• Lambda
• Cloud
• Databricks
• Docker
• GCP
• Support
• Machine Learning
• Model Training
• Network
• Python
• Unix

More:

We are Checkout.com, a global fintech company powering digital payments for more than one billion shoppers and over 10 billion transactions each year. Our platform helps ambitious businesses deliver effortless digital experiences at scale, and we work with well-known companies including eBay, Spotify, Klarna, Uber, and Sony. We have 20 offices across six continents, with our headquarters in London, and we offer a hybrid working model with three days per week in the office to support collaboration and connection. We create the conditions for high performers to thrive through real ownership, fewer blockers, meaningful work from day one, and a team culture built on ambition, impact, and mutual support.

last updated 39 week of 2026