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Senior Data Scientist (Fraud)

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Londres
GBP 55 000 - 75 000
Description du poste
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.
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* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.

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