At a Glance
- Tasks: Lead data science initiatives to enhance claims automation and fraud detection.
- Company: Join Marshmallow, a forward-thinking company making migration easier.
- Benefits: Enjoy flexible working, competitive bonuses, and a personal benefits budget.
- Why this job: Make a real-world impact by driving meaningful automation in the claims journey.
- Qualifications: Experience in machine learning and generative AI systems is essential.
- Other info: Embrace a culture of continuous growth and inclusivity at Marshmallow.
The predicted salary is between 70000 - 90000 £ per year.
About Marshmallow
We exist to make migration easy. A systemic problem of this magnitude requires a team of curious thinkers who relentlessly pursue solutions. Those who constantly challenge the why, dismantle assumptions, and always take action to build a better way. A Marshmallow career is built on a cycle of continuous growth, with learning at its core. You will be challenged to raise the bar on your capabilities and supported with the right tools and guidance to do so. This ensures you can deliver impactful work and drive change.
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 Staff Data Scientist who can provide technical leadership 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
- 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.
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
- 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.
Perks of the job
- Flexible working: Spend three days a week with your team in our collaborative London office, and own your own working hours.
- Competitive bonus scheme - designed to reward and recognise high performance.
- Flexible benefits budget - £50 per month to spend on a Ben Mastercard meaning you get your own benefits budget to spend on things you want.
- Mental wellbeing support – Access therapy and mental health sessions through Oliva.
- Learning and development – Personal budgets for books and training courses to help you grow in your role. Plus 2 days a year - on us! - to further your skillset.
- Private health care - Enjoy all the benefits Vitality has to offer, including reduced gym memberships and discounts on smartwatches.
- Medical cash plan - To help you with the costs of dental, optical and physio (plus more!).
- Tech scheme - Get the latest tech for less.
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).
- Systems Design & Technical interview with a couple of the team (90 mins).
- Culture interview (60 mins).
Background checks
As part of our commitment to maintaining a safe and trustworthy environment, we’ll carry out standard background checks, including a DBS and a Cifas check. These help ensure there are no ongoing criminal proceedings and support the prevention of fraud and other forms of serious misconduct.
Everyone belongs at Marshmallow
At Marshmallow, we want to hire people from all walks of life with the passion and skills needed to help us achieve our company mission. To do that, we’re committed to hiring without judgement, prejudice or bias. We encourage everyone to apply for our open roles. Gender identity, race, ethnicity, sexual orientation, age or background does not affect how we process job applications. We’re working hard to build an inclusive culture that empowers our people to do their best work, have fun and feel that they belong.
Recruitment privacy policy
We take privacy seriously here at Marshmallow. Our Recruitment privacy notice explains how we process and handle your personal data.
Staff Data Scientist in London employer: Marshmallow
Contact Detail:
Marshmallow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Marshmallow on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. This insider info can give you a leg up!
✨Tip Number 2
Prepare for your interviews by diving deep into the company’s mission and values. Show us how your skills align with our goal of making migration easy. Tailor your examples to demonstrate your impact in previous roles, especially in data science.
✨Tip Number 3
Practice your technical skills! Brush up on your machine learning and generative AI knowledge. We want to see you in action, so be ready to discuss your past projects and how you tackled challenges in a hands-on way.
✨Tip Number 4
Don’t forget to ask questions during your interviews! This shows us that you’re genuinely interested in the role and the company. Inquire about the team dynamics, ongoing projects, and how you can contribute to our mission.
We think you need these skills to ace Staff Data Scientist in London
Some tips for your application 🫡
Show Your Curiosity: When writing your application, let your curiosity shine through! We want to see how you challenge assumptions and think critically about data science. Share examples of how you've tackled complex problems and what solutions you came up with.
Be Clear and Concise: We appreciate clarity in communication. Make sure your application is easy to read and straight to the point. Highlight your relevant experience and skills without fluff – we want to know how you can contribute to our mission!
Tailor Your Application: Don’t just send a generic application! Tailor it to the Staff Data Scientist role by aligning your experiences with the job description. Show us how your background in machine learning and AI fits perfectly with what we're looking for.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our team at Marshmallow!
How to prepare for a job interview at Marshmallow
✨Understand the Company Mission
Before your interview, dive deep into Marshmallow's mission to make migration easy. Familiarise yourself with their approach to problem-solving and how they value continuous growth. This will help you align your answers with their core values and demonstrate that you're genuinely interested in contributing to their goals.
✨Showcase Your Technical Leadership
As a Staff Data Scientist, you'll need to provide technical leadership. Prepare examples from your past experiences where you've successfully led projects or influenced technical direction. Be ready to discuss how you can apply this experience to shape risk decisioning and fraud detection at Marshmallow.
✨Prepare for Cross-Functional Collaboration
Collaboration is key in this role. Think of specific instances where you've worked closely with Product, Engineering, or Operations teams. Highlight how you communicated effectively and navigated challenges to achieve successful outcomes. This will show that you can thrive in a cross-functional environment.
✨Demonstrate Your Problem-Solving Skills
Marshmallow values those who can think in systems and tackle complex problems. Prepare to discuss how you've approached ambiguity in past projects. Use the STAR method (Situation, Task, Action, Result) to structure your responses, showcasing your ability to bring clarity and momentum to challenging situations.