Data Science Manager

NRG.
Newcastle upon Tyne
3 months ago
Applications closed

Related Jobs

View all jobs

Trainee Sales Manager (Progression to Director)

Business Systems Manager

Data & Analytics Manager

Data Governance Manager

Bus Network Planning Manager

IT Operations Manager

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.

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.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.