Marshmallow

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.

About Us ????

Marshmallow aims to make insurance more accessible and more affordable for as many people as possible ????. That means harnessing technology, automation and intelligent decision making to serve customers better and cheaper than traditional insurers .

We’re here to generate insights and actions from all the data we can get our hands on. This includes analytics, predictive modelling, and prescriptive recommendations. We deliver high impact work to the business, focusing on high risk, high reward projects, and making sure all decisions are data driven.

We’re now looking for a Data Scientist to join our Claims Tribe, where we are on a mission to transform how we handle claims by using data and AI to make faster and smarter decisions that improve outcomes and reduce costs ????.

This is a critical area of the business that directly affects our loss ratio, operational efficiency and customer satisfaction. You will build intelligent systems that help us solve the right claims at the right time for the right cost by combining predictive models, agentic AI workflows and automation to guide and accelerate decisions across the claim lifecycle. That includes decisioning models, fraud detection, prioritisation and workflow logic.

There are high impact problems to solve, and you will be part of a team that is actively redefining what great looks like in claims handling through the use of frontier AI tools and human in the loop systems.

What you’ll be doing ????

• Owning and delivering data science solutions that improve how we triage, prioritise and resolve claims with measurable impact on cost, speed and customer experience.
• Building and deploying predictive models that support automated decisions or enable better human ones (e.g. risk triage, fraud signals, case prioritisation, exception handling).
• Collaborating with engineers, product managers and claims experts to embed your models into our internal systems and tools.
• Supporting an experimentation-first mindset with A/B tests and analytics to prove business value.
• Contributing to the definition of KPIs and analytical processes that help us evaluate and continuously improve claims performance.
• Exploring opportunities to apply emerging AI technologies such as agentic systems and large language models to streamline workflows and assist decision makers in real time.

Who you are ????

• You are naturally curious and hands-on, all things data and ML related.
• You have a commercial mindset and focus on driving meaningful business impact.
• You communicate clearly across both technical and non-technical teams.
• You care about the customer journey and want to make hard moments easier.
• You’re pragmatic and outcome-oriented, not wedded to complexity for its own sake.
• You enjoy solving real operational problems with cutting edge tools, especially where human judgment and automation intersect.
• You value simplicity, clarity, and strong data foundations.

What we're looking for from you ????

Experiences that are essential ????

• Experience building and deploying ML models that deliver measurable business results.
• Understanding of how to evaluate performance within risk decisioning, including performance trade-offs and operational considerations.
• Familiarity with A/B testing and measuring model impact.
• Proficiency in Python and SQL.
• At least 2+ years of professional experience in data science or similar roles.

Experiences that will help you ????

• Experience in insurance, operations, or other complex service environments.
• Experience working with unstructured data (e.g. documents, free text, images).
• Knowledge of MLOps best practices and model monitoring.
• Experience with experimentation frameworks and KPI tracking.
• Strong communication skills.
• PhD or masters degree from a top institution.
• Experience designing, building and deploying Generative AI applications or Retrieval-Augmented Generation (RAG) systems in operational or customer facing 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 Marília, 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.