Data Science Manager

NRG.
Newcastle upon Tyne
1 year ago
Applications closed

Related Jobs

View all jobs

Data Science Manager

Data Science Manager - Telematics

Data Science Lead / Manager

Senior Manager, Data Science - eBay Live

Junior Data Engineer (Data Science)

Data Science & Machine Learning - Senior Associate - Asset Management

Job Opportunity: Data Science Manager

Location:Newcastle Upon Tyne


Client:A leading digital insurance provider with ambitious plans to become a market leader in the UK.


About the Role

Our client is seeking a Data Science Manager to lead cutting-edge projects and develop predictive models that enhance pricing strategies. The role involves working with a combined team of Actuaries and Data Scientists, utilizing machine learning (ML) to extract valuable insights from extensive customer data.


Key Responsibilities:

  • Develop and maintain best-in-class predictive models for claims outcomes, fraud, and other KPIs.
  • Engineer new rating factors for integration into pricing algorithms.
  • Identify and monetize new data sources.
  • Manage and mentor junior team members.
  • Lead the delivery of analytical tools and strategic projects.


Requirements:

  • Proven experience in predictive modeling, including Gradient Boosting Machines (GBMs), within a General Insurance pricing environment.
  • Proficiency in Python and core Data Science libraries.
  • Strong interest in emerging ML techniques.
  • Experience in end-to-end delivery of large model reviews.


What’s on Offer:

  • Salary:Competitive
  • Flexible Working:Hybrid options available.
  • Bonus:Annual performance bonus tied to business and personal performance.
  • Benefits:27 days of annual leave (plus bank holidays), healthcare cash plans, dental cover, tech schemes, and more.


Culture and Values:

The company fosters a collaborative environment based on its 4Cs principles: supporting colleagues, delighting customers, growing the company, and giving back to the community.


Additional Information:

This role is not eligible for sponsorship. Candidates will be subject to credit and criminal record checks.

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.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.