Data Science Manager - Insurance (Propensity models)

Bromley
2 days ago
Create job alert

Data Science Manager (Insurance, Propensity Models, Python) £90,000 - £120,000 plus excellent benefits including a 14% bonus and 10% pension

Location: Bromley, Kent 2 days in the office
Contract Type: Permanent

Are you a talented Data Science professional looking to take your career to the next level? A leading financial institution in the insurance sector is seeking a dynamic Data Science Manager to join their Actuarial team. If you're passionate about leveraging data science to drive business strategy and have a strong background in propensity models, we want to hear from you!

About the Role:

In this exciting brand new role, you'll be at the forefront of building and implementing innovative data science solutions that align with our client's strategic goals. You'll have previous experience of strong Stakeholder engagement and collaborate closely with various stakeholders across the globe, including Business Solutions, Distribution Channels, Marketing, and Actuarial teams. This opportunity is perfect for someone with a quantitative background looking to enhance their commercial experience within the life insurance sector.

Key Responsibilities:

Identify growth opportunities and optimise in-force processes using data science.

Conduct investigations utilising data science applications and present insights to stakeholders.

Lead the training and development of Machine Learning models, including propensity models.

Integrate CRM systems with Machine Learning models for effective data analysis.

Build predictive modelling solutions to implement actionable initiatives across the business.

Support ongoing business management by exploring opportunities around data strategy.

Collaborate with distribution channels to enhance performance management through data analytics.

Ensure compliance with internal and external requirements, including Group AI Policy and Consumer Duty.

What We're Looking For:

Experience: 5-7 years in a quantitative role, ideally within the insurance or financial services sector.

Skills: Proficiency in Python, R, SPSS Modeller, and data visualisation tools like Power BI, Tableau, or Qlik.

Expertise: Ability to build Machine Learning models from scratch with strong documentation and governance.

Communication: Strong relationship management skills and the ability to explain technical subjects to senior stakeholders.

If you're ready to make a significant impact in the world of data science within the insurance industry, apply now! Join us in shaping the future of our client's data-driven initiatives and unlock your potential in a role that values innovation and collaboration.

Apply today send your CV to (url removed) and embark on an exciting journey with us! We can't wait to see how you can contribute to our client's success

Related Jobs

View all jobs

Engineering Manager

Data Analytics Manager

Lead Data Manager | Healthcare Sector | Cambridge

Data & Analytics Manager

Data Warehouse Manager

Data Manager

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Shadowing and Mentorship in AI: Gaining Experience Before Your First Full-Time Role

How to Find the Right Mentors, Maximise Your Learning, and Position Yourself for a Successful AI Career The artificial intelligence (AI) field is expanding at a remarkable pace, offering countless opportunities to innovate, create, and make a meaningful impact across a variety of sectors. From healthcare and finance to retail and cybersecurity, AI is rapidly becoming an integral part of modern society. As demand for AI talent continues to surge, securing your first full-time role can feel both exciting and daunting. Many aspiring AI professionals wonder how to gain relevant experience to stand out among a sea of job applicants. This article explores the concept of shadowing and mentorship—two invaluable strategies that can help you acquire hands-on knowledge, build confidence, and connect with influential figures in the AI industry. By the end of this piece, you’ll not only understand how to identify potential mentors but also know how to nurture these relationships and showcase your value as a mentee, propelling you closer to your ultimate goal of landing your first AI job.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.