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- Tasks: Lead the design of pricing algorithms and risk models in a dynamic insurtech environment.
- Company: Join a growing insurtech revolutionising insurance pricing with innovative technology.
- Benefits: Enjoy a competitive salary, hybrid work options, and a supportive team culture.
- Why this job: Shape the future of pricing while working on impactful projects with autonomy and collaboration.
- Qualifications: 2+ years in data science or pricing, strong Python and SQL skills required.
- Other info: Flexible start date in September; work in a vibrant London office near Liverpool Street.
The predicted salary is between 47000 - 64000 £ per year.
Location: London (near Liverpool Street)
Sector: Insurtech | Risk Pricing & Claims Modelling
Join a well-backed, growing insurtech on a mission to reimagine how insurance pricing is done. This business is building out a cutting-edge risk modelling function—and they’re hiring their first Data Scientist in pricing to help lead the charge. You’ll work directly with the Pricing & Data Science Manager, taking full ownership of pricing algorithm design, risk modelling, and technical rate setting. This is a high-impact role offering strong autonomy, a supportive team, and the opportunity to shape the pricing function from the ground up.
What you’ll be working on:
- Designing and deploying machine learning models to price technical risk and claims
- Modelling claims data to improve rate accuracy and reduce customer churn
- Working across third-party and low/no-code platforms to streamline pricing tools
- Supporting the wider data team and collaborating closely with underwriting and product
- Building clean, scalable solutions using Python, SQL, and modern ML frameworks
What we’re looking for:
- 2+ years’ experience in a data science or pricing role within insurance
- Strong skills in Python, SQL, and ML libraries such as scikit-learn or XGBoost
- Proven experience modelling claims, risk, or technical pricing
- Confident working independently and comfortable shaping processes from day one
- Bonus: experience with low/no-code pricing tools or supporting data engineering work
The setup:
- Hybrid: 2–3 days/week in their central London office (Liverpool Street)
- Interview process: 2 stages – virtual 1-to-1, followed by senior stakeholder session
- September start date is fine for candidates with notice periods
You’ll be part of a supportive, collaborative team with plenty of projects ready to go.
Data Scientist employer: Intellect Group
Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in insurtech and risk pricing. Understanding the current landscape will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Brush up on your Python and SQL skills, especially focusing on libraries like scikit-learn and XGBoost. Being able to discuss specific projects where you've used these tools will set you apart from other candidates.
✨Tip Number 3
Prepare to showcase your experience in modelling claims and technical pricing. Think of concrete examples where your work has led to improved rate accuracy or reduced customer churn, as these are key aspects of the role.
✨Tip Number 4
Since the role involves collaboration with underwriting and product teams, be ready to discuss how you've successfully worked in cross-functional teams in the past. Highlighting your teamwork skills will be crucial.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and pricing, particularly within the insurance sector. Emphasise your skills in Python, SQL, and any machine learning libraries you've used.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for insurtech and your understanding of risk pricing. Mention specific projects or experiences that demonstrate your ability to design and deploy machine learning models.
Showcase Relevant Projects: If you have worked on projects related to claims modelling or technical pricing, include them in your application. Provide brief descriptions of your role and the impact of your work.
Prepare for Interviews: Research common interview questions for data scientists in the insurance industry. Be ready to discuss your experience with machine learning models and how you approach problem-solving in pricing scenarios.
How to prepare for a job interview at Intellect Group
✨Showcase Your Technical Skills
Make sure to highlight your experience with Python, SQL, and machine learning libraries like scikit-learn or XGBoost. Prepare examples of projects where you've successfully designed and deployed models, especially in the context of insurance pricing.
✨Understand the Business Context
Familiarise yourself with the insurtech sector and the specific challenges related to risk pricing and claims modelling. Being able to discuss how your skills can directly impact the company's mission will impress the interviewers.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would approach designing a pricing algorithm or improving rate accuracy, and be ready to explain your thought process.
✨Demonstrate Collaboration Skills
Since the role involves working closely with underwriting and product teams, be prepared to discuss your experience in collaborative environments. Share examples of how you've worked with cross-functional teams to achieve common goals.
