Senior Data Scientist - Casualty Analytics

About Willis Towers Watson:

Willis Towers Watson (NASDAQ: WTW) is a leading global advisory, broking, and solutions company that helps clients around the world turn risk into a path for growth. With roots dating to 1828, Willis Towers Watson has 45,000 employees serving more than 140 countries and markets.

We design and deliver solutions that manage risk, optimize benefits, cultivate talent, and expand the power of capital to protect and strengthen institutions and individuals. Our unique perspective enables us to identify the critical intersections between talent, assets, and ideas — the dynamic formula that drives business performance.

Together, we unlock potential.

About the team:

The Direct and Facultative Data and Analytics team offer a wide range of analytical support to the broking team in order to secure the best results for our clients. Typical analytical support includes data management, catastrophe modelling, exposure management, financial modelling, and bespoke analytics. The focus of our team is to provide brokers with a deeper understanding of their client's risk from natural and man-made perils such as windstorm, earthquake, severe convective storm, flood and wildfire.

About the role : In this senior role, you will partner closely with Brokers in the Global Markets Direct & Facultative team to deliver innovative casualty analytics, pricing systems and decision-support tools. The Direct & Fac Data and Analytics team provides a broad range of analytical insights, models and technology-enabled solutions to help the broking team achieve the best outcome for the client.

Core analytical support includes data transformation, process automation, predictive modelling, workflow optimisation, dashboarding and development of bespoke analytical tools that improve speed, consistency and scalability across casualty analytics and pricing. The role will initially focus on development of analytical processes, building models and tools, and improving how data is captured, validated and used across the team. You will have structured exposure to liability risk pricing so you can grow into pricing ownership over time across commercial auto liability, general liability, worker's compensation and excess casualty lines.

On a day-to-day basis, you will work with complex claims, exposure and portfolio data, design repeatable data and analytics pipelines, develop analytical tools in Python or similar languages, and build solutions that convert raw data into actionable outputs for brokers and stakeholders. The role demands a rigorous, problem-solving mindset, strong coding and modelling capability, and the ability to translate technical outputs into practical business value.

We are looking for candidates with a quantitative or technical degree from a top tier university (statistics, mathematics, engineering, data science, computer science, or similar), strong experience in data analytics or data science, and excellent communication skills to bridge technical delivery with business impact. Prior insurance experience is beneficial but not essential.

Roles and Responsibilities:

This is a general summary of the duties that the individual will be expected to perform as a part of their role:

• Handle, cleanse and structure complex claims, exposure and portfolio data to ensure accuracy, usability and analytics readiness.
• Lead automation of recurring analytical and reporting workflows to improve efficiency, consistency and turnaround times across the casualty analytics process.
• Develop, test and maintain complex statistical models, tools and data solutions using Python, SQL (Structured Query Language.)and related technologies.
• Design and deploy scalable data pipelines, templates and utilities that support pricing, portfolio analysis and stakeholder decision-making.
• Build dashboards and visualisation solutions (e.g., Power BI) that convert analytical outputs into clear and actionable business insights.
• Identify opportunities to streamline manual processes and improve the team’s use of data, analytics and technology.
• Collaborate with brokers, underwriters and other stakeholders to understand business problems and translate them into analytical or technical solutions.
• Support the development and enhancement of casualty pricing models and tools, with the opportunity to build expertise in liability risk pricing over time.
• Validate outputs, monitor model or tool performance and continuously improve solutions based on user feedback and business needs.
• Mentor junior analysts and contribute to continuous improvement initiatives across data, analytics and pricing.