Senior Data Scientist

Checkout.com; Greater London; On-site; GBP 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid working model

Job summary

Checkout.com is seeking an experienced Senior Data Scientist to lead advanced optimisation projects and shape robust ML architectures that improve payment flows. You will work with senior peers to design scalable models and production-grade Python tools, driving multi-objective optimisation across complex systems.

The role emphasizes collaboration with product stakeholders, distributed data processing using Spark/Dask, and strong emphasis on model explainability.

Qualifications

• 5+ years designing, building and maintaining ML models for large-scale business problems.
• Deep understanding of frequentist and Bayesian statistics and modelling techniques.
• Production-grade Python coding and collaboration with non-technical stakeholders.

Responsibilities

• Lead multi-objective optimisation projects and architecture for scalable models.
• Create custom loss functions, evaluation frameworks and tuning methods.
• Collaborate with product stakeholders to align tech strategy with business goals.
• Apply distributed data transformations using Spark or Dask with robust test coverage.
• Mentor junior team members and drive feature improvements via explainability.

Skills

ML model development

Statistics (frequentist & Bayesian)

Model explainability

Production Python

LLM-assisted coding

Stakeholder communication

Distributed computing (Spark/Dask)

Product collaboration

Tools

Docker

AWS/GCP

Job description

About the Role

Checkout.com is looking for an experienced Senior Data Scientist to lead advanced optimisation projects and champion the development of robust, sustainable ML architectures. You will be responsible for enhancing payment flow through data and ML services, advancing the complex problem of multi-objective optimisation. You will work closely with other Senior and Staff Data Scientists to shape the architecture of our decisioning systems.

Key Responsibilities

• Lead projects and architecture design for multi-objective optimisation and scalable models.
• Create custom loss functions, evaluation, and tuning frameworks that reflect complex business problems.
• Collaborate with product stakeholders to align technical strategy with business goals and resolve blockers across the team.
• Apply efficient data transformations using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems.
• Mentor junior team members and utilise model explainability methods to drive feature performance improvements.

About You

• 5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems.
• Deep understanding of frequentist and Bayesian statistics, plus supervised and unsupervised modelling techniques.
• Proven experience modelling complex interactions (e.g., cluster or network effects).
• Expertise in model explainability to tune feature engineering and understand feature interactions.
• Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical stakeholders.
• Proficient in leveraging LLMs for coding support and process optimisation to maximise personal and team productivity.
• Adept at tuning technical communication for broad audiences.
• Proven ability to build trusting relationships with product stakeholders and deeply understand business models.

Nice to have

• Experience with distributed general‑purpose cluster‑computing.
• Proven experience designing and deploying recommender systems, contextual bandits, or network intelligence applications.
• Experience in fintech, payments or similar domains.
• Experience with Docker, AWS/GCP, and modern ML deployment practices.

Benefits

We offer a hybrid working model with flexibility and three days per week in the office to support collaboration and connection.