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Marshmallow is a fintech unicorn (founded 2017, 700+ employees, £140M raised, profitable) on a mission to make migration easy. The company has scaled from insuring millions of drivers to offering car loans and broader financial services, with ambitions to become one of the world's largest financial services providers.
The Data Science team partners across the business to turn data into better decisions, smarter products, and simpler customer journeys. This Staff Data Scientist role sits within Claims, one of Marshmallow's most important customer touchpoints, and focuses on automating the claims journey through technical leadership in traditional ML and Generative AI.
Key Responsibilities:
- Provide technical leadership for data science across Claims Fraud, shaping risk decisioning and fraud detection in partnership with Product and Engineering
- Design, build, and iterate on production ML and Generative AI/LLM systems supporting claims validation and automation
- Collaborate with other Claims data scientists to bring system-level thinking to how models, data, and workflows integrate, identifying architectural improvements to scale decisioning and reduce time-to-production
- Advocate for platform and tooling investments (monitoring, feedback loops, QA) needed to achieve AI-driven end-to-end claims automation
- Champion robust, scalable, and strategically aligned technical solutions in cross-functional discussions, ensuring systems contribute to the multi-year vision for automated claims handling
- Set high standards for statistical rigor, experimentation, and measurement, improving how Claims performance and uncertainty are understood and communicated to senior stakeholders
You think in systems and can connect data science, engineering, and product to shape scalable solutions. You're confident challenging assumptions and pushing for the right approach, using strong communication to influence stakeholders across seniority levels. You thrive in ambiguity and change, bringing structure and clarity to complex problems. You're motivated by real-world impact and partner closely with cross-functional teams to drive meaningful automation and better customer outcomes.
Requirements:
- Significant commercial experience delivering end-to-end Machine Learning solutions, from problem framing and experimentation through production deployment and ongoing monitoring
- Hands-on experience building and shipping Generative AI systems in production (not prototypes), including evaluation, safety/quality considerations, and integration into customer or operational workflows
- Strong statistical and modeling foundation, with experience in risk-based decisioning under uncertainty (e.g., fraud, credit, insurance, or other regulated domains)
- Proven ability to influence technical direction across Data Science and Engineering, including shaping scalable model/service integration patterns and challenging proposals to drive robust, long-term solutions
- Strong stakeholder management skills, with confidence communicating trade-offs and pushing back constructively with Product and Engineering to ensure high-quality outcomes
The role is hybrid (3 days in office, London). Visa sponsorship is available. Benefits include bonus scheme, private medical insurance with Vitality, mental health support with Oliva, personal learning budget, 2 dedicated L&D days per year, monthly flexible benefits budget, 25 days holiday plus bank holidays, and 4 weeks Work From Anywhere per year.
