Arqiva
Head of Data Science

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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.
Location
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.
What’s in it for you
- 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.
Accountabilities
Set the direction
- 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
Deliver measurable business impact
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
- 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 and lead a high-performing team
- 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
Champion AI across the organisation
- 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
Skills / Experience
- 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 operationalising 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 obstacles.
- Strong stakeholder management skills, with the ability to influence at executive level and translate technical complexity into clear business outcomes and action.


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Our Tech Stack
You'll be joining a team that has invested heavily in a modern, cloud-native data and AI platform. We build on Databricks Lakehouse and AWS, using technologies such as Python, PySpark, dbt, MLflow, Unity Catalog and modern CI/CD practices to take ideas from experimentation to production.
Our data scientists work alongside data engineers, architects and product teams on a shared platform, with access to the tooling needed to develop machine learning, generative AI and agentic AI solutions at enterprise scale.
Our Commitment
We believe great data science goes beyond algorithms. It requires curiosity, collaboration, and responsibility. You’ll play a key role in ensuring we use data and AI in a way that is ethical, transparent, and trusted.
Why Arqiva
We enable a switched-on world to flow. As the UK’s leader in TV and radio broadcast and the country’s top smart utilities platform, we are shaping the future of connectivity.
Our infrastructure delivers media and data exactly where they’re needed - whether that’s bringing TV and radio to your home or sending smart meter data to your utility provider. Our technology works quietly behind the scenes, connecting millions every day.
But it’s not just what we do, it’s how we do it. At Arqiva, you’ll find real connection: supportive teams, active colleague networks and plenty of ways to get involved and feel part of our community. We’ll give you the space and support to grow - whether that’s developing your skills, trying something new or taking on fresh challenges. And because there is more to life than work, our rewards and benefits are designed to support your wellbeing, your lifestyle and what matters most to you.
Our commitment to Diversity & Inclusion
At Arqiva, we’re committed to building a workplace where everyone feels valued, heard and empowered to succeed. We welcome applications from all backgrounds and experiences, and we work hard to remove barriers so every colleague can thrive. If you need any adjustments at any stage of the recruitment process, please reach out to talent@arqiva.com.
If this sounds like the right next step for you, we’d love to hear from you!
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