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For Companies At a Glance
- Tasks: Lead a data science team to develop machine learning solutions for insurance.
- Company: Join a globally recognised insurer known for innovation and collaboration in the Lloyd’s market.
- Benefits: Enjoy a hybrid work model and a culture that values innovation and growth.
- Why this job: Make impactful decisions and lead exciting projects in a supportive environment.
- Qualifications: Experience in Data Science or Actuarial roles, with strong leadership and technical skills required.
- Other info: Opportunity to shape the future of data-driven underwriting in a respected company.
The predicted salary is between 43200 - 72000 £ per year.
Join a high-performing, globally recognised insurer in the Lloyd’s market — known for its disciplined underwriting, long-term partnerships, and collaborative culture. Our client blends innovation with tradition, offering a dynamic environment where data-driven insights are shaping the future of insurance.
We’re hiring a Data Science Manager to lead the design, development, and deployment of machine learning and advanced analytics solutions. You’ll play a critical role in transforming how underwriting, pricing, and risk assessment are executed, using data science to drive smarter decisions and digital trading strategies. You’ll manage a team of skilled data scientists and work hand-in-hand with underwriters, actuaries, engineers, and business leaders to turn complex data into actionable insights and measurable outcomes.
What You’ll Be Doing
- Lead and grow a high-impact data science team within the Lloyd’s insurance ecosystem.
- Build and productionise machine learning models to support risk selection, pricing, and underwriting automation.
- Collaborate with actuarial and digital trading teams to analyse portfolios and enhance pricing sophistication.
- Implement AI/ML techniques to automate processes and strengthen data pipelines.
- Develop strategic data assets and visualisation tools that empower underwriters.
- Partner with IT and engineering to integrate analytics into core platforms.
- Define best practices for model governance, deployment, and monitoring.
- Contribute to internal governance and model approval processes.
What We’re Looking For
- Experience in Data Science or Actuarial roles, ideally within Lloyd’s or the wider insurance industry.
- Strong leadership capabilities with experience managing teams and engaging senior stakeholders.
- Deep understanding of statistical modelling, machine learning, and data science frameworks.
- Expert-level proficiency in Python; familiarity with version control and collaborative development workflows.
- Experience with Azure tools (e.g. Data Factory, Synapse, SQL, Power BI) highly desirable.
- Proven track record of delivering analytics solutions in collaboration with data engineers and IT teams.
- Degree in a quantitative field such as Mathematics, Statistics, Computer Science, or similar.
Why Apply?
- Influence core business decisions at one of the most respected insurers in the Lloyd’s market.
- Lead exciting projects that combine traditional underwriting with cutting-edge analytics.
- Thrive in a supportive environment that values innovation, ownership, and long-term growth.
Ready to Make an Impact?
Take the next step in your career and help shape the future of data-driven underwriting. Apply now to join a company where data science drives real-world outcomes.
Data Science Manager - Insurance employer: Stott and May
Contact Detail:
Stott and May Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager - Insurance
✨Tip Number 1
Network with professionals in the Lloyd's insurance market. Attend industry events, webinars, or meetups to connect with potential colleagues and leaders in data science and insurance. Building these relationships can provide valuable insights and may lead to referrals.
✨Tip Number 2
Showcase your leadership skills by sharing examples of how you've successfully managed teams or projects in the past. Highlight any experience you have in collaborating with cross-functional teams, especially in a data-driven environment, as this is crucial for the role.
✨Tip Number 3
Familiarise yourself with the latest trends and technologies in machine learning and data science, particularly those relevant to the insurance sector. Being able to discuss current innovations and how they can be applied to underwriting and risk assessment will set you apart.
✨Tip Number 4
Prepare to discuss specific projects where you've implemented AI/ML techniques. Be ready to explain the challenges you faced, the solutions you developed, and the impact your work had on the business. This practical knowledge will demonstrate your capability to drive results.
We think you need these skills to ace Data Science Manager - Insurance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and the insurance industry. Emphasise your leadership skills and any specific projects where you've successfully implemented machine learning solutions.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and its application in the insurance sector. Mention specific examples of how you've led teams or projects that align with the role's requirements.
Highlight Technical Skills: Clearly list your technical proficiencies, especially in Python and Azure tools. Provide examples of how you've used these skills to deliver analytics solutions in previous roles.
Showcase Collaboration Experience: Discuss your experience working with cross-functional teams, such as underwriters and actuaries. Highlight how your collaborative efforts have led to successful outcomes in past projects.
How to prepare for a job interview at Stott and May
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll need to demonstrate strong leadership capabilities. Be prepared to discuss your experience managing teams and engaging with senior stakeholders. Share specific examples of how you've successfully led projects or initiatives in the past.
✨Highlight Technical Proficiency
Make sure to emphasise your expert-level proficiency in Python and familiarity with Azure tools. Be ready to discuss your experience with statistical modelling and machine learning frameworks, as well as any collaborative development workflows you've been part of.
✨Understand the Insurance Landscape
Since this role is within the Lloyd’s market, it's crucial to have a solid understanding of the insurance industry. Brush up on current trends, challenges, and innovations in underwriting and risk assessment to show that you're well-informed and passionate about the field.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and ability to apply data science techniques in real-world situations. Think of examples where you've used data-driven insights to influence business decisions or improve processes, and be ready to discuss them in detail.
