At a Glance
- Tasks: Use advanced analytics to enhance risk selection and pricing in specialty insurance.
- Company: Join a leading global specialty insurer with a focus on innovation.
- Benefits: Competitive salary, great benefits, and opportunities for professional growth.
- Why this job: Make a real impact by shaping data-driven decisions in the insurance industry.
- Qualifications: Experience in data science, statistical modelling, and strong communication skills.
- Other info: Dynamic work environment with a focus on collaboration and career development.
The predicted salary is between 60000 - 80000 £ per year.
Locations: UK - London (St Botolph)
Time Type: Full time
Posted on: Posted Today
Job Requisition ID: 2026-262
Reporting to: Head of Pricing
Stakeholders: Underwriting, Claims, Pricing, IT/Data
Standing still is not an option in the current world of Insurance. TMHCC are one of the world’s leading Specialty Insurers. With deep expertise in our chosen lines of business, our unparalleled track record and a solid balance sheet, TMHCC evaluates and manages risk like no one else in the industry. Looking beyond profit, empowering our people and delivering on our commitments are at the core of our customer values, and so is a desire to grow and provide creative and innovative solutions to our clients.
Job Purpose: The role will apply advanced analytics and modelling to improve risk selection, pricing decisions, and claims insight across speciality insurance lines (e.g. Renewables, D&O, Credit and Marine). This role sits at the intersection of underwriting judgement, actuarial thinking, claims insight, and modern data science. It focuses on practical impact - building insights, tools and models that are understood, trusted and used by the business. The first 12 months will involve a secondment into the Innovation team, helping shape a cross-line analytics capability that strengthens decision-making across the underwriting lifecycle.
Key Responsibilities:
- Partner with underwriting, pricing, and claims teams to frame complex business problems where data is incomplete, judgement is central, and risk characteristics are heterogeneous.
- Design, develop, validate, and explain models appropriate for low-frequency, high-severity specialty risks, with particular focus on improving risk selection and portfolio quality.
- Engineer and test features derived from underwriting, exposure, claims, financial, catastrophe, ESG, and external datasets.
- Translate analytical outputs into clear decision support, explicitly communicating uncertainty, assumptions, and limitations.
- Support experimentation in pricing and risk assessment approaches while maintaining defensibility and alignment with governance expectations.
- Collaborate with data engineering and application developer colleagues to support deployment, monitoring, and scaling where production use is appropriate.
- Contribute to the development of a consistent, cross-line analytics capability embedded within Pricing and Innovation.
Key Deliverables:
- Underwriters, pricing teams, and claims colleagues actively use and trust data science outputs to improve risk selection and portfolio outcomes.
- Models and insights are explainable, defensible, and aligned with underwriting logic and regulatory expectations.
- Clear collaboration patterns exist between data scientists, actuaries, underwriters, and engineers.
- A credible analytics capability is embedded across specialty lines.
Skills and Experience Specification:
Hard Skills:
- Strong applied data science capability (using Python/R to apply statistical modelling and machine learning techniques) including model design, feature engineering, validation, version control and documentation, with key focus on transparency and explainability throughout.
- Sound statistical and analytical foundations (probability theory, GLMs, time series analysis) and comprehensive understanding of modern machine learning techniques and modelling approaches (e.g. random forest, XGBoost, GBMs).
- Experience working with complex, sparse, or imperfect datasets.
- Solid SQL, data handling and data visualisation skills.
Soft Skills:
- Ability to navigate ambiguity and structure loosely defined business problems.
- Commercial judgement and ability to balance sophistication with practicality.
- Clear and pragmatic communicator, able to build trust in data-driven decision support.
- Strong stakeholder engagement skills across underwriting, pricing, claims, and senior management.
- Ability to work effectively with data and software engineers.
- Curiosity and adaptability across different specialty classes and risk cultures.
What We Offer: The Tokio Marine HCC Group of Companies offers a competitive salary and employee benefit package. We are a successful, dynamic organization experiencing rapid growth and are seeking energetic and confident individuals to join our team of professionals. The Tokio Marine HCC Group of companies is an equal opportunity employer.
Applied Data Scientist (Specialty Insurance) employer: Tokio Marine HCC
Contact Detail:
Tokio Marine HCC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Data Scientist (Specialty Insurance)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at TMHCC or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for interviews by practising your storytelling skills. You want to showcase your data science projects and how they’ve made an impact. Make it relatable and show how your work aligns with their goals in specialty insurance.
✨Tip Number 3
Don’t just apply and wait! Follow up on your applications through our website. A quick email expressing your enthusiasm can set you apart from the crowd and show you're genuinely interested.
✨Tip Number 4
Stay curious and adaptable! The world of data science is always evolving, especially in niche areas like specialty insurance. Keep learning and be ready to discuss new trends or tools during your interviews.
We think you need these skills to ace Applied Data Scientist (Specialty Insurance)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Applied Data Scientist role. Highlight your experience with Python/R, statistical modelling, and any relevant projects that showcase your skills in data science and analytics.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about specialty insurance and how your background aligns with our mission. Be sure to mention specific examples of how you've tackled complex business problems using data.
Showcase Your Soft Skills: While technical skills are crucial, don’t forget to highlight your soft skills too! We value clear communication and stakeholder engagement, so share experiences where you’ve successfully collaborated with teams or navigated ambiguity.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows your enthusiasm for joining our team!
How to prepare for a job interview at Tokio Marine HCC
✨Know Your Data Science Stuff
Make sure you brush up on your applied data science skills, especially in Python or R. Be ready to discuss your experience with statistical modelling and machine learning techniques, as well as how you've tackled complex datasets in the past.
✨Understand the Insurance Landscape
Familiarise yourself with specialty insurance lines like Renewables, D&O, Credit, and Marine. Knowing the nuances of these areas will help you frame your answers and demonstrate your understanding of the industry during the interview.
✨Communicate Clearly
Practice explaining your analytical outputs in a way that’s easy to understand. You’ll need to convey uncertainty, assumptions, and limitations clearly, so think about how you can make complex concepts accessible to non-technical stakeholders.
✨Show Your Collaborative Spirit
Be prepared to discuss how you’ve worked with cross-functional teams in the past. Highlight your stakeholder engagement skills and give examples of how you’ve built trust with underwriters, pricing teams, and claims colleagues through effective communication.