Senior Data Scientist - Multi-Objective ML for Payments

Checkout; Greater London; Hybrid; GBP 100,000 - 140,000; Full time

Job summary

Checkout.com is seeking an experienced Senior Data Scientist to lead advanced optimisation projects and champion robust ML architectures. You will enhance payment flow through data and ML services, advancing multi-objective optimisation while working with other Senior and Staff Data Scientists on decisioning systems.

You will collaborate with product stakeholders, apply distributed computing, and mentor the team to improve feature performance using explainability methods.

Qualifications

• 5+ years of designing, building and deploying ML models for large-scale business problems.
• Strong understanding of frequentist and Bayesian statistics and modelling techniques.
• Proven ability to model complex interactions (e.g., cluster or network effects).
• Expertise in model explainability to guide feature engineering and interactions.
• Ability to write production-grade Python and communicate with non-technical stakeholders.
• Experience using LLMs for coding support and process optimisation.

Responsibilities

• Lead multi-objective optimisation projects and scalable model architecture.
• Create custom loss functions, evaluation, and tuning frameworks for business problems.
• Collaborate with product stakeholders to align technical strategy with business goals.
• Apply distributed data transformations (Spark, Dask) and ensure robust production tests.
• Mentor juniors and drive feature performance improvements with explainability.

Skills

Machine Learning

Python

Distributed computing

Model explainability

Stakeholder collaboration

LLMs

Technical communication

Tools

Spark

Dask

Docker

AWS/GCP

Job description

Checkout.com is seeking an experienced Senior Data Scientist to lead advanced optimisation projects and champion robust ML architectures. You will enhance payment flow through data and ML services, advancing multi-objective optimisation while working with other Senior and Staff Data Scientists on decisioning systems.

You will collaborate with product stakeholders, apply distributed computing, and mentor the team to improve feature performance using explainability methods.