Location
London or Reigate office, with the office location agreed during onboarding. You may be expected to travel to other WTW locations for team or client meetings.

Hours
Full Time - In-person learning is valued, so attendance in the office at least four days a week is expected.

Salary
Negotiable

About the Role
Join WTW’s Insurance Consulting and Technology (ICT) team and be part of impactful projects from day one. The ICT team combines deep insurance consulting expertise with innovative technology, working across actuarial pillars within Property and Casualty (P&C) including reserving, capital, and pricing, as well as data science, process transformation, risk and regulatory, climate, exposure management, underwriting, and claims analytics. You will work on client projects, research, and product development.

Working alongside market-leading experts, you will apply data science techniques to analyse data and deliver insightful results. You will present your findings internally and to clients, collaborate with UK and global colleagues, and build core technical skills through hands-on experience and team support. Your projects will involve developing, assessing, and deploying machine learning models, writing high-quality code, and using both open-source tools and WTW’s proprietary insurance technology solutions widely used in the insurance market.

You will also benefit from structured early-career training and ongoing learning from subject matter experts, helping you grow your expertise and career in data science within insurance consulting.

Experience
Experience in a coding or data-processing language such as Python, R, SQL or similar is required. Exposure to concepts such as Retrieval-Augmented Generation ("RAG") and Agentic AI is beneficial but not required.

About you
Highly numerate and analytical with a strong interest in extracting value from data and solving complex commercial problems. Genuinely interested in recent advancements in data science, including Machine Learning and Generative AI. A clear and confident communicator able to explain complex ideas to diverse audiences. Personable, approachable, motivated to work collaboratively in a supportive team environment. Eager to learn and develop new ideas. Comfortable using AI tools with an understanding of their strengths and limitations.

Qualifications
At least a 2:1 degree in a numerate discipline. A-level Mathematics at grade A or above, and at least 136 UCAS points across three A levels or equivalent qualifications (for example, AAB or A*AC meets the overall points requirement).