marshmallow - Senior Data Scientist
Requirements
• You think in systems: you can connect the dots between data science, engineering, and product to shape scalable solutions that build on each other over time. • You're confident in challenging assumptions and pushing for the right approach, using strong communication skills to influence stakeholders across seniority levels and disciplines with clear, pragmatic reasoning. • You thrive in ambiguity and change, staying resilient and effective during transitions while bringing structure, clarity, and momentum to complex problem spaces. • You're motivated by real-world impact, partnering closely with cross-functional teams to drive meaningful automation and better customer outcomes across the claims journey. • 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
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 • 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 • We are able to offer visa sponsorship for this position. • Initial call with a member from our Talent Team (30 mins) • Past Experience interview with Hiring Manager (60 mins) • Technical interview with a couple of the team (90 mins) • Culture interview (60 mins) • Diversity of thought • We know the best ideas come from having different perspectives in the room - and we're committed to hiring fairly, regardless of background, identity or experience. If you see yourself in this role, we'd encourage you to apply.
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