Responsibilities
- Build and iterate on multimodal AI models that reduce claims cost and improve claims processing, including models that analyse emails, documents, and claim summaries for operational teams
- Develop machine learning models that support claims automation, including use cases such as negotiation strategies, litigation strategies, and total loss prediction
- Explore and evaluate new data sources that could improve model performance and decision-making, such as fraud signals, open banking, and telematics data
- Design and build agentic AI solutions to automate and streamline claims workflows
- Collaborate closely with Product, Data, and Engineering teams to test hypotheses, develop new features, and turn ideas into production-ready solutions
- Work with the MLOps team to improve data science and AI model infrastructure, including deployment, monitoring, evaluation, and feedback loops
- Help define the right technical approach for problems, balancing speed, quality, and scalability while ensuring solutions are practical for the business
- Set a strong standard for experimentation, measurement, and model performance, helping the team understand impact, uncertainty, and trade-offs clearly
Requirements
- Strong commercial experience delivering end-to-end machine learning solutions, from problem framing and experimentation through to production deployment and ongoing monitoring
- Hands-on experience building and shipping production AI or machine learning systems, including evaluation, quality considerations, and integration into operational workflows
- Experience working on applied problems involving structured and unstructured data, with an interest in multimodal modelling and AI systems
- A strong statistical and modelling foundation, with experience working on risk-based decisioning or other complex, uncertain problem domains
- Proven ability to work cross-functionally with Product, Engineering, Operations, and MLOps to deliver scalable solutions
- Strong communication and stakeholder management skills, with confidence in discussing trade-offs and pushing back constructively when needed
Benefits
- Bonus scheme designed to reward high performance
- Private medical insurance with Vitality, mental health support with Oliva
- Personal learning budget and 2 dedicated L&D days a year
- Monthly flexible benefits budget to spend as you choose
- 25 days holiday plus bank holidays
- 4 weeks Work From Anywhere per year
Work Arrangement
Hybrid — London
Visa sponsorship available
