Lead Pricing Data Scientist

Marshmallow
LondonPosted 21 April 2026

Tech Stack

Job Description

Lead Pricing Data Scientist We exist to make migration easy. Every year, millions of people move to a new country and find themselves cut off from essential financial services. We built our own technology to change that, insuring millions of drivers and lending millions in loans. But we're not standing still. Our ambitions are huge, and we need exceptional people to supercharge our growth and shape what comes next. Marshmallow is a place for do-ers. People who are tenacious, hungry for ownership, and unfazed by complexity. But collective success always comes first - people here win and grow together. Pricing at Marshmallow Pricing at Marshmallow is where the mission gets real — delivering unbeatable prices that make migration easy. You'll work with vast, proprietary data, cutting-edge models, and engineers who can implement your ideas fast. Ownership isn't a buzzword here — you'll have the autonomy to make decisions and the senior backing to act on them. This is a team that moves fast, challenges assumptions, and delivers change at high frequency. WHAT YOU’LL BE DOING - Develop a deep understanding of Marshmallow’s quote, policy, and claims data to derive insights that enhance pricing strategies. - Contribute to key pricing initiatives, including expansion plans and customer retention efforts. - Communicate analytical findings effectively to senior leaders and cross-functional teams. - Conduct data analysis using SQL and Python to drive decision-making. - Support the deployment of models in APIs for real-time pricing applications. - Collaborate with pricing team members to recommend changes and track their impact. - Assess new external data sources to refine claims risk evaluation and quantify their value. - Monitoring the performance of our business and contributing to our governance and control processes such as reviewing business mix and segmental loss ratio performance. - Work closely with Engineering and ML Engineering teams to implement pricing strategies. WHO ARE YOU? - Proactive: You want to drive growth by identifying new opportunities and take ownership to drive change - Technical: You aren’t afraid to learn new skills across Data Science & Insurance - Commercial: You want to deliver real world impact, not report on it - Curious: You aren’t satisfied with ‘That’s just how it is’; you immediately investigate further - Opinionated: You generate your own opinions & pitch to others in an open & honest way - Explainer: You can communicate complicated concepts in a simple way to non-experts WHAT SKILLS ARE WE LOOKING FOR FROM YOU? - Ability to interrogate data and conduct pricing analysis within SQL & Python - Ability to build GLMs, GBMs and other models within Python - Prior experience in a data science role or STEM degree OUR PROCESS We break it up into 3 stages: - Initial screening call with a member of the TA team (30 mins) - Past experience interview with our VP Insurance(60 minutes) - A technical interview (90 mins) - A culture interview with a senior stakeholder to check that your work style fits our processes and values, and vice versa (60 mins) PERKS OF THE JOB - Hybrid working - Spend 2-3 days with the team in our collaborative London office, and own your own working hours. 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 💰 - 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, inc ... (truncated, view full listing at source)
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