National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Scientist (Fraud) | London, UK

Marshmallow
London
1 week ago
Create job alert

About Marshmallow

We build financial products that accelerate the economic freedom for people who move across borders. We started with car insurance - insuring over a million drivers - and we're scaling beyond. Tens of millions of people move countries each year, facing overlooked financial challenges. Our future is in building financial products around their needs to positively impact their lives.

How we work

We're really proud of the culture we've created. We push for progress every day, because we know that we'll only hit big milestones by taking lots of smaller steps. We're always open to helping our team mates, sharing our ideas, experience and knowledge to solve problems together. We take risks, think creatively and experiment relentlessly to meet our customer's needs, and never pass blame when things go wrong. We encourage people at all levels to take ownership of their work, and to be bold in challenging how we do things. Everyone has a voice and the opportunity to make an impact.
And autonomy and ownership are only possible with clear direction. That's why we collaborate to do in-depth planning twice a year, and make sure we leave with clear goals and objectives that flow from top to bottom. To make sure we're as aligned as possible across functions, most of our work rolls up into three tribes; Acquisition, Retention & Claims. Each tribe has multiple teams embedded in it, working cross-functionally to do great work.
We're so excited for all of the challenges up ahead, and we need more people to help us tackle them! If life at Marshmallow sounds like it could be for you, explore our Culture Handbook to find out more.

The Fraud Team

We are here to use data and AI to protect Marshmallow from application fraud, making sure that the people and risks we insure are genuine and fairly priced. Our work is critical to achieving a healthy loss ratio, unlocking growth, and building trust with under-served customer segments.

Our focus is on policy fraud at the point of sale. That includes detecting misrepresentation, organised fraud such as ghost broking, and verifying customer information efficiently and at scale. We build models and tools that help Marshmallow validate customer information, automate document reviews, and direct investigative effort to where it has the biggest impact. The goal is to reduce operational workload while improving decision quality.

You will join a cross-functional team spanning fraud operations, product, and engineering, with full ownership of your initiatives. You will help shape the next generation of fraud defences powered by intelligent workflows, structured and unstructured data, and a strong focus on experimentation and results. Success in this role requires deep technical skill, curiosity about fraud behaviours, and the ability to turn insight into action.

What you'll be doing

  • Building and deploying models to detect application fraud and misrepresentation, particularly at quote and policy inception.
  • Using structured and unstructured data including documents and images to automate fraud checks and reviews.
  • Partnering with product and ops to embed risk-based decisioning and triage into our fraud platform.
  • Improving how we prioritise fraud reviews through smarter routing / decisioning logic that balances loss ratio impact with operational cost and customer experience.
  • Evaluating the impact of interventions through A/B tests and automated decision tooling.
  • Feeding fraud intelligence into model development, working closely with our in-house investigations and analytics teams.
  • Contributing to the evolution of our fraud infrastructure and helping to shape its use across multiple Marshmallow products.


Who you are

  • You are naturally curious about fraud and interested in how it evolves in the real world.
  • You care deeply about business impact and think commercially when deciding how to apply your skills.
  • You are pragmatic about delivery and understand when good enough is better than perfect.
  • You are a strong communicator and collaborator across both technical and non-technical teams.


What we're looking for from you

Experiences that are essential

  • Background in fintech, insurance, or similar industries with exposure to fraud or credit risk.
  • Experience building and deploying ML models that deliver measurable business results.
  • Experience working with unstructured data (documents, images).
  • Understanding of how to evaluate performance within risk decisioning, including performance trade-offs and operational considerations.
  • Proficiency in Python and SQL and confidence working with large datasets.
  • At least 3 to 4 years of professional experience in data science or similar roles.


Experiences that will help you

  • Experience working on car insurance fraud or understanding of fraud risks in insurance pricing and onboarding.
  • Knowledge of industry tools such as Onfido, SIRA, IFB data, or graph-based fraud detection platforms.
  • Experience deploying fraud solutions into customer-facing products or automated decision systems.
  • Awareness of how to balance fraud prevention with customer experience and operational efficiency.
  • Familiarity with document and identity verification processes.
  • Experience designing, building and deploying Generative AI applications or Retrieval-Augmented Generation (RAG) systems in production environments.


Perks of the job

  • Flexi-office working- Spend 2-3 days a week with your team in our new collaborative London office. The rest is up to you!
  • 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. Whether that's subscriptions, night classes (puppy yoga, anyone?), the big shop or a forest of houseplants. Pretty much anything goes
  • Sabbatical Leave -Get a 4-week fully paid sabbatical after being with us for 4 years
  • Work From Anywhere- 4 weeks work from anywhere to use, with no need to come to the office
  • 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


Plus all the rest; 33 days holiday, pension, cycle to work scheme, monthly team socials and company-wide socials every month!

Our process

We break it up into a few stages:

  • Initial call with our Talent Acquisition Partner - 30 mins
  • A past experience interview where you will discuss your journey so far and ways of working with Pawel, our hiring manager - 60 mins
  • A technical interview with a couple of the team - 90 mins
  • A culture interview with a bar raiser to see if your work style fits our processes and values (and vice versa!) - 60 mins


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. To find out more please view it here.

Boost your careerFind thousands of job opportunities by signing up to eFinancialCareers today.
#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.