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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 in a collaborative setting.
- Qualifications: 2+ years in data science or pricing, with strong Python and SQL skills required.
- Other info: Opportunity to start in September; flexible interview process.
The predicted salary is between 47000 - 67000 £ 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
- 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
- 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.
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
Network with professionals in the insurtech space, especially those working in data science or pricing roles. Attend industry meetups or webinars to make connections that could lead to valuable insights or referrals.
✨Tip Number 3
Brush up on your Python and SQL skills, focusing on libraries like scikit-learn and XGBoost. Consider working on personal projects or contributing to open-source projects to showcase your technical abilities.
✨Tip Number 4
Prepare for the interview by thinking about how you would approach designing a pricing algorithm. Be ready to discuss your thought process and any relevant experiences that highlight your problem-solving skills.
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. Use keywords from the job description to demonstrate that you meet their specific requirements.
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 align with the responsibilities outlined in the job description.
Showcase Technical Skills: In your application, emphasise your proficiency in Python, SQL, and machine learning libraries. Consider including examples of past projects where you successfully applied these skills, especially in modelling claims or technical pricing.
Prepare for Interviews: Anticipate questions related to your experience with machine learning models and risk modelling. Be ready to discuss how you've worked independently and contributed to shaping processes in previous roles.
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 implemented these skills, especially in the context of insurance pricing or risk modelling.
✨Understand the Business Context
Research the insurtech sector and understand how pricing algorithms impact the business. Be ready to discuss how your work can contribute to improving rate accuracy and reducing customer churn, as this will demonstrate your alignment with their mission.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about challenges you've faced in previous roles, particularly related to claims data modelling or technical pricing, and how you overcame them.
✨Emphasise Collaboration and Autonomy
Since the role involves working closely with various teams, be prepared to discuss your experience in collaborative environments. Highlight instances where you've taken ownership of projects while also supporting team efforts, showcasing your ability to balance independence with teamwork.
