Staff Data Scientist

Staff Data Scientist

Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
Marshmallow

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 customer journeys.
  • 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.
  • 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.

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 employer: Marshmallow

At Marshmallow, we pride ourselves on fostering a culture of continuous growth and innovation, making it an exceptional place for a Staff Data Scientist to thrive. With flexible working arrangements, a competitive bonus scheme, and a strong emphasis on mental wellbeing and professional development, our London office is designed to support your career while you contribute to meaningful automation in the claims journey. Join us to collaborate with curious thinkers and make a real impact in the migration space.
Marshmallow

Contact Detail:

Marshmallow Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Data Scientist

✨Tip Number 1

Network like a pro! Reach out to current or former employees at Marshmallow on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.

✨Tip Number 2

Prepare for the interview by diving deep into Marshmallow's mission and values. Show us how your skills align with our goal of making migration easy. Tailor your examples to highlight your experience in data science and collaboration.

✨Tip Number 3

Practice your storytelling! We love candidates who can articulate their journey and impact clearly. Use the STAR method (Situation, Task, Action, Result) to structure your answers and keep it engaging.

✨Tip Number 4

Don’t forget to ask questions during your interview! This shows your interest and helps you gauge if Marshmallow is the right fit for you. Think about what you want to know about our culture, team dynamics, and future projects.

We think you need these skills to ace Staff Data Scientist

Machine Learning
Generative AI
Statistical Analysis
Risk Decisioning
Data Science
Technical Leadership
Stakeholder Management
Problem Framing
Production Deployment
Monitoring and Evaluation
Cross-Functional Collaboration
Communication Skills
Adaptability
System-Level Thinking

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 in the past.

Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your experience with Machine Learning and Generative AI. We appreciate a well-structured application that highlights your skills without unnecessary fluff.

Tailor Your Application: Make sure to customise your application for the Staff Data Scientist role. Highlight relevant experiences that align with our mission at Marshmallow, especially in claims automation and risk decisioning. Show us why you're the perfect fit!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!

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 Culture Handbook and think about how your skills as a Staff Data Scientist can contribute to this goal. Being able to articulate how you align with their mission will show your genuine interest in the role.

✨Showcase Your Technical Leadership

Prepare to discuss your experience in providing technical leadership, especially in data science. Be ready to share specific examples of how you've shaped risk decisioning or fraud detection in previous roles. Highlight your hands-on experience with Generative AI systems and how you've integrated them into operational workflows.

✨Communicate Clearly and Confidently

Since the role requires influencing stakeholders across various levels, practice articulating complex ideas in a clear and concise manner. Think about how you can challenge assumptions constructively and push for the right approach while maintaining strong communication with Product and Engineering teams.

✨Prepare for System-Level Thinking

Given the emphasis on system-level thinking in the job description, come prepared with examples of how you've connected data science, engineering, and product to create scalable solutions. Be ready to discuss architectural improvements you've identified in past projects and how they contributed to reducing time-to-production.

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