Principal Data Scientist

Marshmallow

Principal Data Scientist providing technical leadership for Claims automation and fraud detection at Marshmallow. Delivering machine learning solutions and collaborating across teams to enhance claims processes.

Posted 7/9/2026full-timeLondon • 🇬🇧 United KingdomLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in delivering end-to-end Machine Learning solutions and building production-level Generative AI systems, with a strong foundation in statistical modeling and risk-based decisioning. Capable of influencing technical direction and advocating for scalable, robust solutions in cross-functional environments.

Highest-signal resume keywords

End-To-End Machine Learning SolutionsGenerative AI Systems DevelopmentStatistical Modeling and Risk DecisioningStakeholder ManagementTechnical Leadership in Data Science

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningGenerative AIStatistical AnalysisModelingRisk DecisioningExperimentationProduction DeploymentMonitoringData IntegrationAutomation

Soft Skills

Stakeholder CommunicationInfluencing Technical DirectionConstructive FeedbackCollaborationProblem Framing

Tools & Technologies

AI PlatformsMonitoring ToolsFeedback LoopsQuality Assurance ToolsData Science Frameworks

Industry Keywords

Claims FraudRisk ManagementInsuranceRegulated DomainsOperational Workflows

About the role

Key responsibilities & impact

Provide technical leadership for data science across Claims Fraud, shaping the approach to risk decisioning and fraud detection in partnership with Product and Engineering
Design, build and iterate on production ML and Generative AI/LLM systems that support claims validation and automation
Collaborate closely with other Claims data scientists to bring system-level thinking to how models, data and workflows fit together, identifying architectural improvements needed to scale decisioning and reduce time-to-production
Be vocal about the platform and tooling investments needed (monitoring, feedback loops, QA) to achieve AI-driven end to end claims automation
Advocate for robust, scalable, and strategically aligned technical solutions in cross-functional discussions, ensuring current systems and infrastructure contribute to the multi-year vision for automated claims handling
Set a high bar for statistical rigour, experimentation and measurement, helping improve how Claims performance and uncertainty are understood and communicated to senior stakeholders

Requirements

What you’ll need

Significant 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 Generative AI systems in production (not just prototypes), including evaluation, safety/quality considerations, and integration into customer or operational workflows
Strong statistical and modelling 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.

Benefits

Comp & perks

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