Data Scientist – ML for Payment Performance

About the role

Checkout.com is seeking a Data Scientist to design, experiment and deploy new estimators, models and features that improve payment performance for its global merchant portfolio. The role works closely with product, engineering and fellow data scientists to protect customer lifetime value and ensure safe model launches.

Key responsibilities

• Research and develop new machine‑learning models and estimators to boost core acceptance‑rate performance.
• Design and run experiments that manage time‑based data leakage and provide robust model evaluation.
• Collaborate with engineers to productionise ML features, models and evolve evaluation and monitoring frameworks.
• Write high‑quality, interpretable Python code for feature engineering and model training that directly supports core products.
• Communicate hypotheses, evaluation results and monitoring dashboards clearly to technical and non‑technical audiences.

Required profile

• 3+ years of experience developing machine‑learning models to solve business problems.
• Strong understanding of supervised ML algorithms, hyper‑parameter tuning and performance evaluation.
• Experience with feature‑engineering techniques such as target encoding.
• Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation.
• Proven ability to write clean, production‑grade Python code for both training and inference.
• Enthusiasm for leveraging large language models to improve coding productivity.

Required skills

• Python
• Databricks
• Docker
• Google Cloud Platform (GCP) or Amazon Web Services (AWS)
• Unix shell scripting
• Lambda functions
• Large language models (LLMs)