Head of Data Science

Description Head of Data Science Purpose

We’re entering a new era where AI is no longer experimental - it’s operational, embedded, and transformative. From large-scale machine learning to generative AI and intelligent automation, data science is now central to how we innovate, compete, and deliver value.

As Head of Data Science, you will define and lead our data science vision - translating cutting‑edge AI capabilities into real-world business impact. You’ll shape how advanced analytics, ML, and emerging AI technologies are applied across the organisation, ensuring we move beyond pilots into scaled, production‑grade AI solutions.

This is a rare opportunity to lead a talented and ambitious team while directly influencing strategic outcomes - turning data into decisions, and models into measurable value.

We operate a hybrid working model. This role will require a flexible approach to attending one of our offices, with an expectation of being on-site approximately 1–2 days per week
, depending on business needs, meetings and key stakeholder engagement.

• Up to £115,000
• 15% bonus
• Work Life Smarter – our commitment to a flexible and hybrid working culture
• Generous pension scheme starting at 6% rising to 10%
• A unique wellbeing programme that looks after the whole you
• Access to multiple learning platforms to support your individual development
• Active and diverse networks that build community, support wellbeing and advocate for change
• A comprehensive set of benefits including discounts on big brands, gymflex memberships and paid volunteering leave - see our full list of benefits here.

Plus, you’ll play an integral role in protecting the commercial value of Arqiva’s sites - a critical part of how we deliver for our customers.

• Define and lead a forward-looking data science and AI strategy aligned to business priorities
• Partner with senior stakeholders to translate ambition into clear, investable roadmaps
• Identify where emerging AI capabilities - such as generative AI, foundation models, and intelligent agents - can unlock competitive advantage

• Lead the development of advanced analytics, machine learning, and AI solutions that solve complex business problems
• Ensure solutions are production-ready, scalable, and embedded into business workflows
• Oversee the full lifecycle - from problem shaping through to deployment and value realisation
• Drive adoption of modern practices such as MLOps, model monitoring, and responsible AI governance

• Develop, mentor, and inspire a team of data scientists and ML engineers
• Foster a culture of experimentation, continuous learning, and applied innovation
• Set a high-performance bar - focused on outcomes, impact, and measurable value

• Act as a trusted advisor and translator between technical and business audiences
• Promote best practice in data ethics, AI governance, and model transparency
• Stay at the forefront of industry developments - bringing in new tools, platforms, and ways of working

• Proven experience leading and developing data science teams, creating an environment where people can learn, grow and deliver value.
• A track record of delivering AI and machine learning solutions that have achieved measurable business outcomes, not just technical proofs of concept.
• Deep hands‑on expertise across machine learning, advanced analytics and modern data platforms (e.g. Databricks, Snowflake), with the ability to contribute directly when needed.
• Practical experience taking models from experimentation to production, with a strong understanding of what works, what doesn't, and the trade‑offs involved in delivering AI at scale.
• Experience ope rationalising models using robust engineering, MLOps and model governance practices.
• Strong knowledge of emerging AI technologies, including large language models, generative AI and agentic AI, combined with the judgement to separate genuine opportunities from hype.
• The ability to balance strategic thinking with hands‑on delivery, helping teams solve complex problems and overcome technical…