Principal Data Scientist – Machine Learning & AI

Our team tackles a broad range of machine learning and AI problems. Depending on business priorities, you may work on projects such as:

Predictive modeling for pricing, underwriting, claims, catastrophe risk, and portfolio management

Classification, ranking, matching, recommendation, and anomaly detection systems that improve business decision-making

Information extraction from documents, emails, forms, and other unstructured data using modern AI techniques

Entity resolution, data enrichment, and building high-quality datasets from noisy or incomplete information

Design AI systems that automate analytical and decision-making workflows end to end. Build the measurement that tells us whether they genuinely outperform what they replace

Building production feature pipelines, model inference services, and evaluation frameworks

Collaborating with engineers, actuaries, underwriters, product managers, and business leaders to turn ambiguous questions into scalable machine learning solutions

You likely have experience with many of the following:

A strong quantitative foundation: statistics, probability, optimisation, or applied mathematics

Sound modelling judgement - you know what it takes for a model to hold up in the real world, not just on a validation set

Strong programming skills

Real willingness to work with LLMs and agentic AI as everyday tools, wherever your background sits today

Clear communication with both technical and non-technical audiences - you can explain a lift curve to an underwriter and a shrinkage prior to a statistician