Data Scientist

Prima
City of London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Consumer Lending Data Scientist

Data Scientist - Imaging - Remote - Outside IR35

Data Scientist (Predictive Modelling) – NHS

Data Scientist - New

Are you looking for a new challenge?


Fancy helping us shape the future of motor insurance?


Prima could be the place for you.


Since 2015, we’ve been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we’ve quickly become the number one online motor insurance provider. In fact, we’re trusted by over 4 million drivers. And now we’re expanding to help millions more drivers in the UK and Spain.


To help fuel that growth, we need a Data Scientist to join our Pricing & Underwriting UK team, that is the strategic engine behind Prima's growth.


As part of this team, you’ll play a key role in shaping our business strategy and driving innovation. By combining advanced analytics and machine learning, you’ll help keep our pricing competitive and our risk under control. You’ll work at the intersection of data science and real-world impact, collaborating with cross-functional teams to turn insights into action.


Excited to make an impact? Here are the details
What you'll do

  • Translating business challenges into data problems and designing practical, data-driven solutions, from identifying pricing opportunities to improving how we assess risk;
  • Building and adapting predictive models, from traditional statistical approaches to advanced machine learning, grounded in a strong understanding of their theoretical foundations and their application to insurance pricing;
  • Delivering actionable solutions by translating modelling insights into production-ready tools and processes, working closely with experienced Machine Learning and Data Engineers, and leveraging cutting-edge technology and best practices.

What we're looking for

  • A strong academic background in Mathematics, Physics, Engineering, Statistics, or a related quantitative field;
  • Exceptional quantitative, logical, and analytical abilities, with a knack for solving complex problems;
  • A growth-oriented mindset, with a strong desire to learn quickly and develop expertise in data science, programming and business skills.

Nice-to-have

  • Proficiency in programming, particularly with Python, and experienced in data querying and analysis, particularly with SQL;
  • Familiarity with programming best practices, such as version control using Git and implementing unit tests;
  • Experience in data science with machine learning algorithms and applying them in line with industry best practices.

Why you’ll love it here

We want to make Prima a happy and empowering place to work. So if you decide to join us, you can expect plenty of perks.


🤸 Work Your Way: Enjoy hybrid working, with a mix of home and office days. Plus, for up to 30 days per year, work from anywhere.


🏁 Grow with us: We may move fast at Prima, but we move together. Get access to learning resources, mentorship and a growth plan tailored to you.


🌈 Thrive and perform: Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs and mental health support.


Think you’re a match? Apply now.


At Prima, we celebrate uniqueness. If you don’t meet every requirement but are passionate about this role, we still want to hear from you. Innovation thrives on diverse perspectives.


Prima is proud to be an equal opportunity employer. Need accommodations during the process? Email us at . Let’s build the future of insurance, together.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.