Machine Learning & Statistics

• Solid grounding in machine learning, supervised and unsupervised methods, and classical statistical techniques. Comfortable working with probabilistic models, uncertainty estimation, and Bayesian inference.

Model Development

• Understanding of the full model training pipeline, including data preparation, feature selection, model selection, and model validation.

Experience

• Hands-on experience building and evaluating models in a data science or quantitative context.

Python & SQL

• Comfortable using Python and SQL for data exploration, feature development, and modelling workflows.

Communication

• Able to present findings clearly to both technical and non-technical audiences.

Nice to Haves

Simulation

• Experience with Monte Carlo methods or probabilistic simulation.

AI Integration

• Comfortable using AI-assisted coding tools such as Claude Code or Cursor as part of your everyday workflow, and open to integrating them deeper into how you model and build.

What We Look For

Curiosity

• You are naturally curious about the “Why”. You look at data and customer behavior to inform your decisions.

Collaborative & Open

• You treat your work as a starting point for collaboration. You contribute to shared knowledge and code bases, and value engaging with your peers to build solutions.

Continuous Development

• You are keen to develop knowledge and skills, keeping up to date with relevant developments and applying new learning where appropriate.

What We Offer

• Hybrid working out of our London office (Farringdon) - most of our staff come into the office about twice a week
• Salary based on our external benchmarking framework, plus eligibility for a bonus scheme
• Private health insurance, occupational life cover, and income protection insurance
• Personal days, including birthdays and health and wellness days
• AI forward culture including Claude Code Premium subscription