Senior Data Scientist

We’re on a mission to make migration easy.

We started building Marshmallow in 2017. Since then, we’ve grown from 3 to 700+ people, gained unicorn status, raised ~£140M over three funding rounds, turned profitable, insured millions of drivers and lent millions in car loans.

But we’re only just getting started. Our goal is to become one of the largest financial services providers in the world. Over the next 10 years we’ll grow exponentially, not only by scaling our existing products, but also by building new ones.

To achieve our goals we need incredibly ambitious, commercially driven people who never settle for ‘good enough’. Marshmallowers are hungry for autonomy and ownership, and would rather improve than coast. Everyone raises standards and has an impact, with a focus on collective success over self-interest.

We’ve created an environment where curious, tenacious people win and grow together. If that sounds motivating, this could be the place for you.

London (hybrid, 3 days in office)

Data Science at Marshmallow

Our Data Science team partners across the business to turn data into better decisions, smarter products, and simpler customer journeys. We work closely with Product, Engineering, and Operations to build and ship models and AI systems that are reliable in production and deliver measurable impact.

Within Data Science, this role sits in Claims , supporting the function and the broader ambition to automate more of the claims journey. Claims is one of Marshmallow's most important customer touchpoints, and we're looking for a Senior Data Scientist who can provide technical expertise across traditional ML and Generative AI, bring system-level thinking to how we scale decisioning, and confidently challenge proposals to ensure we build robust, sustainable solutions.

What you'll be doing

• 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

Who You Are

• 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.

What You'll Bring

• 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

Perks of the job

• 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.

Our process

• 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.