Data Science and Analytics Manager

Reading
1 day ago
Create job alert

Data Science & Analytics Manager
Remote Based

About the Opportunity

We are recruiting for an experienced Data & Analytics Manager to lead and evolve an organisation’s analytics capability within a highly technical, innovation-focused environment.

This is a strategic leadership role with real influence. You will shape how data science is applied across complex systems, drive performance improvements through advanced modelling, and support the development of next-generation technologies. You will collaborate with internal engineering teams, external partners, and academic institutions while building and mentoring a high-performing analytics function.

The Role

You will take ownership of end-to-end analytics delivery — from identifying opportunities and sourcing data through to modelling, simulation, deployment, and performance evaluation.

Key responsibilities include:

  • Leading the identification and adoption of advanced data science and analytics capabilities to improve organisational performance.

  • Overseeing the full lifecycle of analytics solutions, including development, validation, deployment, and monitoring.

  • Providing expert guidance on complex analytical challenges, selecting appropriate data sources and modelling approaches.

  • Leading large-scale data initiatives, including sourcing, preparing, validating, and exploiting internal and external datasets.

  • Applying modelling and simulation techniques to generate theoretical performance predictions.

  • Developing robust test methodologies to assess real-world system performance.

  • Analysing measured outcomes and providing clear recommendations to inform design improvements.

  • Designing and evaluating correlation, fusion, and rule-based logic algorithms to support performance assessment.

  • Establishing and promoting data science standards, governance, and best practice.

  • Supporting and developing data scientists through structured task definition, objective setting, and performance oversight.

  • Working closely with cross-functional teams and external collaborators to ensure successful project delivery.

    Skills & Experience

    We are looking for a technically strong and commercially aware analytics leader with:

  • A proven background in analysis, modelling, and simulation within technology-driven or security-focused environments.

  • Strong experience applying statistical modelling techniques to complex, real-world datasets.

  • Excellent proficiency in SQL, Python, R, VBA, and SAS.

  • Experience managing data requirements, analytical workflows, and structured data models.

  • The ability to communicate complex findings clearly and confidently to both technical and non-technical audiences.

  • Demonstrated leadership capability, including overseeing analytical delivery and developing team members.

  • A creative, inquisitive mindset with the confidence to challenge assumptions and propose innovative solutions.

    Experience within advanced monitoring, aerospace, defence, or critical infrastructure environments would be advantageous but is not essential.

    Why Apply?

    This is a high-impact leadership role where you will shape analytics capability at an organisational level. You will work on technically challenging programmes, influence advanced technology development, and operate within a collaborative, forward-thinking team.

    If you are an experienced analytics leader looking for a role with real ownership and strategic influence, we would welcome your ap

Related Jobs

View all jobs

Data Science Manager - Advanced Analytics & AI

AI & Data Science Manager / Senior Manager

Senior Data Scientist - AI Practice Team

Senior Data Scientist - AI Practice Team

Senior Geospatial Data Scientist

Global Banking & Markets - Data Scientist / Machine Learning Scientist, Marquee Sales Strats - Associate

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 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.

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.

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.