Junior Pricing Data Scientist

We started building Marshmallow in 2017. Since then, we’ve grown from 3 to 700+ people, gained unicorn status, raised ~£140M over three funding rounds, turned profitable, insured millions of drivers and lent millions in car loans. But we’re only just getting started. Our goal is to become one of the largest financial services providers in the world. Over the next 10 years we’ll grow exponentially, not only by scaling our existing products, but also by building new ones. To achieve our goals we need incredibly ambitious, commercially driven people who never settle for ‘good enough’. Marshmallowers are hungry for autonomy and ownership, and would rather improve than coast. Everyone raises standards and has an impact, with a focus on collective success over self-interest. We’ve created an environment where curious, tenacious people win and grow together. If that sounds motivating, this could be the place for you.

London (hybrid, 3 days in office). We are not able to offer visa sponsorship for this position.

About the team: Marshmallow's pricing team applies quantitative methods to real insurance problems. In this role, you'll learn how pricing decisions work in practice and turn data into meaningful outcomes. You'll work closely with a senior pricing team member, bringing your quantitative background into an industry setting. The aim is for you to develop the practical judgement and independence to take on – and eventually lead – increasingly substantial work.

What you'll be doing:

• Working closely with pricing colleagues on scoped analytical and data-driven projects, taking on more responsibility as your experience develops.
• Applying mathematical, statistical and machine learning techniques to practical pricing questions, connecting your analysis to the decision it needs to inform.
• Explaining your findings clearly, keeping colleagues from different areas of the business updated on progress and following up on agreed actions.
• Using feedback to improve your work and build your understanding of data science methods, coding best practice and the commercial context of insurance pricing.

Who you are:

• You want to learn, seek feedback and build towards working independently.
• You communicate your rationale and findings clearly, and keep colleagues informed about your progress.
• You follow through on agreed actions and take ownership of your work.

What you’ll bring:

• A strong academic record and a research master's or PhD in a quantitative field, such as mathematics, physics or econometrics.
• Experience applying quantitative methods or machine learning to a practical problem through your studies, research, a personal project or work.
• Industry experience is preferred - a placement, internship or experience whilst studying, or in between research masters / PhD.
• The ability to explain how your approach fits the problem, rather than relying on theory alone.

Perks of the job:

• Bonus scheme designed to reward high performance.
• Private medical insurance with Vitality, mental health support with Oliva.
• Personal learning budget and 2 dedicated L&D days a year.
• Monthly flexible benefits budget to spend as you choose.
• 25 days holiday plus bank holidays.
• 4 weeks Work From Anywhere per year.

Our process:

• Initial call with a member from our Talent Team (30 mins).
• Combined Past Experience & Technical interview (90 mins).
• Onsite Culture interviews (90 mins).

Diversity of thought: We know the best ideas come from having different perspectives in the room - and we’re committed to hiring fairly, regardless of background, identity or experience.