Head of Data Science | Mostly Remote | Greenfield / New Team

Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Head of Data Science

Head of Data Science

Data Science Manager – Property Tech – London

Lead Data Scientist

Head of Data Science

Head of Data Science

Head of Data Science | Mostly Remote | Greenfield / New Team | Cambridgeshire 

Are you ready to lead a greenfield data science initiative and shape the future of innovation in a dynamic, data-driven industry? This role offers a unique chance to deliver transformative solutions, build and lead a high-performing team, and drive the development of cutting-edge digital platforms. We're looking for a hands-on visionary who thrives on solving complex challenges and turning ideas into impactful outcomes.

The OpportunityAs Head of Data Science, you'll be instrumental in developing a platform that sets the standard for digital expertise in its sector. This is your chance to define the roadmap, lead the development of innovative solutions, and ensure the delivery of measurable value across the business and its stakeholders.

Your Key ResponsibilitiesLeadership

Provide day-to-day direction and leadership to the data science team, driving performance and fostering a collaborative team spirit.
Identify opportunities to leverage data for meaningful productivity gains, building and delivering solutions that make a real difference.
Manage relationships with key technology providers and strategic partners.Greenfield Roadmap & Innovation
Lead the design and implementation of impactful data science functionalities, aligning with the broader strategic direction.
Collaborate with stakeholders to identify and develop capabilities that deliver service value and competitive advantage.
Be a thought leader in leveraging data-driven tools, including advanced machine learning and AI, to address complex challenges.Hands-On Development & Governance
Develop and deploy advanced data science solutions, maintaining best practices and quality throughout the process.
Define the technical requirements to enable seamless implementation and deployment of new capabilities.
Ensure compliance with relevant data legislation, standards, and risk management practices.What We’re Looking ForSkills & Experience
Proven experience leading data science and technical product development teams.
Expertise in programming languages such as Python, R, Julia, and SQL, alongside solid knowledge of machine learning, AI, and big data solutions.
Familiarity with the Microsoft Azure platform and the complete data product lifecycle.Mindset
A hands-on leader passionate about driving innovation.
Strategic thinker with the ability to execute complex projects from inception to release.
Collaborative and proactive, with a commitment to maintaining high professional standards

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.