Wind Hazard Modelling Lead - Climate ML & Insurance Analytics

Professional Services (Banking, Finance, Insurance & Law)

Join a collaborative Knowledge Transfer Partnership (KTP) between the University of Leeds and Lloyds Banking Group. As the KTP Associate, you will lead the development of innovative windstorm hazard models, applying climate science, machine learning and advanced analytics to support insurance risk assessment and decision-making. Working across academia and industry, you will translate cutting-edge research into practical solutions that deliver real business impact.

• Lead the development and implementation of advanced windstorm hazard modelling approaches within Lloyds Banking Group's insurance operations
• Manage, process, and analyse large and complex climate, hazard, and insurance-related datasets to support model development and validation Develop and apply state-of-the-art machine learning and statistical techniques to downscale windstorm hazards to local scales and improve hazard forecast calibration
• Translate cutting-edge academic research in climate science, hazard modelling, and machine learning into robust, scalable, and operational commercial tools
• Work collaboratively with academic supervisors and industry stakeholders in high impact teams to ensure research outputs are aligned with business requirements and operational constraints
• Support the integration of advanced climate risk methodologies into underwriting, pricing, capital modelling, and wider insurance decision-making processes
• Communicate complex scientific and technical concepts clearly to both specialist and non-specialist audiences across the organisation
• Engage effectively with a wide range of stakeholders across Lloyds Banking Group, including senior leadership, technical specialists, and operational teams
• Take ownership of project planning, delivery, reporting, and risk management to ensure successful achievement of project objectives and milestones
• Contribute to the dissemination and embedding of project knowledge, tools, and best practice throughout the organisation
• Operate effectively within both a structured implementation workstream and a broader exploratory research environment, demonstrating adaptability, initiative, and problem-solving capability
• Prepare technical reports, presentations, and project documentation for internal and external stakeholders
• Maintain awareness of emerging developments in climate science, machine learning, catastrophe modelling, and insurance risk analytics to inform project innovation and impact. Represent the project and partnership professionally in meetings, workshops, and dissemination activities with industrial and academic partners.
• Act as the main point of contact in a developing relationship between Lloyds Banking Group and the School of Earth and Environment at Leeds University

• A PhD or close to completion (i.e. submitted at the time of application) in a relevant quantitative field such as Atmospheric or Climate Science, or Fluid Dynamics
• Excellent scientific computational skills in a Linux environment including python programming and machine learning experience
• Experience of handling complex climate, or comparable datasets
• Experience of statistical methods applicable to the evaluation of climate data including weather extremes
• Evidence of producing research of an excellent academic standard
• Evidence of strong interest in applying research to solve real world problems
• Excellent time management skills and evidence of the ability to prioritise tasks to meet deadlines
• Agility and responsiveness to work in a fast-paced environment and respond to requests at short notice
• Excellent team working and collaboration skills
• Evidence of the ability to successfully communicate complex academic information to a range of audiences, including non-specialists, in oral and written formats
• Experience of working with an industry partner (e.g. a CASE award, industrial placement, previous joint academia-industry research)
• Experience of analysing data from initialised climate predictions

This exciting 24-month KTP project aims to transform how UK windstorm risk is assessed within insurance operations. By combining climate science, hazard modelling and machine learning, the project will develop next-generation approaches to understanding and managing weather-related risks. The successful candidate will play a key role in embedding these tools within Lloyds Banking Group, helping to improve resilience to a changing climate while generating benefits for customers, insurers and wider society.

Lloyds Banking Group is one of the UK's leading financial services organisations, serving millions of customers across brands including Lloyds Bank, Halifax, Bank of Scotland and Scottish Widows. Through its General Insurance division, the organisation protects more than 2.5 million UK households, helping customers manage risk and recover from adverse events. Lloyds Banking Group is committed to innovation, sustainability and supporting long-term resilience in the face of emerging climate challenges.