Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

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

Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Head of Data Science

Principal Data Scientist

Lead Data Scientist

Head of Data Science & Analytics

Head of Data Science

Head of Data Science Technology (Product, Engineering, Design) · London ·

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.