National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Actuary / Data Scientist [High Salary]

Compre Group
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Developer

Senior Python Developer

Senior Vehicle Performance Engineer

Senior Data Engineer

Senior Operational Analyst

Senior Solutions Architect

Senior Actuary / Data Scientist Department: Data &Technology Employment Type: Permanent - Full Time Location: UK(London) Description We are a fast-growing global reinsurancespeciality company servicing the insurance markets of Lloyd’s,Europe and North America. Due to growth, our Head of Analytics islooking for an Actuary / Data Scientist to join a small teamsupporting the delivery of our analytics vision, strategy androadmap. The ideal candidate will be a qualified Actuary withhands-on experience in delivering data science and machine learningsolutions or an experienced Data Scientist with a strong backgroundin commercial (re)insurance. This unique opportunity blendsactuarial expertise with technology to drive enhanced data-drivendecision-making. Are you an actuary with ideas, innovationambitions and like modern actuarial problem-solving but in amulti-tech team? This could be what you’ve been looking for.Responsibilities 1. Develop data science and machine learningsolutions that provide actionable insights across core functions,with a focus on M&A/underwriting and claims, to solve criticalbusiness challenges. 2. Build strong, collaborative relationshipswith key stakeholders to develop a deep understanding of businessneeds. 3. Collaborate with a multidisciplinary team of technologyand business experts to develop innovative, high-value solutions.4. Proactively explore new methodologies, data sources or 3rd partytools to enhance analytics capabilities and uncover valuableinsights. 5. Lead the development of proof of concepts and quicklycreate analytics and AI prototypes to demonstrate business valueand drive innovation. 6. Ensure alignment of initiatives with thecompany’s enterprise data strategy and broader business goals. 7.Communicate findings and insights effectively to both technical andnon-technical stakeholders, driving informed decision-making.Candidate Requirements 1. Degree in a relevant field such asactuarial science, computer science, mathematics, engineering orrelated disciplines. 2. Demonstrable experience in P&C(re)insurance, with a strong understanding of industry-specificchallenges and opportunities. 3. Experience of developing advancedanalytics or Machine Learning [ML] in at least one of underwriting,pricing reserving or claims. 4. Strong stakeholder managementskills, with the ability to communicate effectively across alllevels of the organization. 5. Commercially focused with avalue-driven mindset, ensuring solutions deliver tangible businessoutcomes. 6. Proven experience of building and deploying scalablepredictive/ML solutions that deliver measurable business value. 7.Proficiency in SQL and Python/R is essential. 8. Hands-onexperience with Databricks and Power BI is desirable. 9.Familiarity with agile methodologies and tools (e.g., Jira, AzureDevOps). 10. Strong problem-solving and analytical skills, withattention to detail and a focus on innovation. 11. Contributingpositively to our culture and values. Benefits Compre is a globalspeciality reinsurance company that offers capital and liabilitysolutions to its clients, providing them with the certainty theyneed on their portfolios. We are known for being trusted partnersto the market and for having a team of experts who collaborate andmaintain discipline in underwriting, ensuring a differentiatedclient experience. As an ambitious business, we are focused onbuilding depth, breadth, and diversity in the talent across ourbusiness to be future-ready. Our clients' needs evolve as themarket changes, which is why we continuously invest in areas suchas data and technology. - Our values are what make us stand out. Wevalue each other, empower and hold ourselves accountable, areauthentic, collaborative and inclusive, and continuously strive forprogress and innovation. Why join us? At Compre, we offer a rangeof benefits and team engagement events and provide a supportiveenvironment for learning and growth. We are intent upon building agreat business, and over the last few years, we have expanded ourmarkets across Europe, Lloyd's, and North America. To keep ourglobally dispersed team connected, we have various employeeresource groups, including Wellbeing, DEI, COMMS and Engagement. Weinvest in our people and offer learning and developmentopportunities for leaders and employees to build confidence andgrow their skill sets. We value teamwork, authenticity, andinnovation, and provide a space for these behaviours to bloom atCompre. Make an impact in a collaborative environment with some ofthe best talent in the industry, while enjoying: - Competitivesalary & annual bonus - A health & wellbeing subsidy (£20per month) (from Day 1) - A generous pension (eligible afterprobationary period) - Private healthcare from BUPA and aHealthcare Cash Plan from Medicash (from Day 1) - Life assurance(from Day 1) - Income protection (from Day 1) - 25 days annualleave (from Day 1) - Cycle to work scheme (from Day 1) - Seasonticket loan (interest-free) (eligible after probationary period) -Electric vehicle scheme (eligible after probationary period) - EAP(Employee Assistance Programme) (from Day 1) - Learning/studysupport and reimbursement for professional memberships - Hybridworking - Employee socials and recognition programme#J-18808-Ljbffr

National AI Awards 2025

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.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.