Time since we first saw it
Day 4
Early. Similar jobs usually come down between day 7 and day 57.
From 10,507 similar postings that came down. Coming down is not always a hire.
London · London, United Kingdom
Actively hiring, first seen by us 4 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: PricingFrom the employer’s posting
Job title: Junior Pricing Data Scientist
We are not able to offer visa sponsorship for this position
Work on scoped analytical and data-driven pricing projects with a senior colleague
Apply mathematical, statistical and machine learning techniques to pricing questions
Explain findings and keep colleagues across the business updated on progress
Use feedback to improve work and build coding and data science skills
Working closely with pricing colleagues on scoped analytical and data-driven projects
Applying mathematical, statistical and machine learning techniques to practical pricing questions
Explaining your findings clearly, keeping colleagues from different areas of the business updated on progress
Using feedback to improve your work and build your understanding of data science methods, coding best practice
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.
The ability to explain how your approach fits the problem, rather than relying on theory alone.
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.
- 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.
Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 4
Early. Similar jobs usually come down between day 7 and day 57.
From 10,507 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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.
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.
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.
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.
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.
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
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. If you see yourself in this role, we'd encourage you to apply.
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London, United Kingdom
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.
London (hybrid, 3 days in office) We are not able to offer visa sponsorship for this position. About the team