National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

AI Governance Lead

Sky
Shadwell
8 months ago
Applications closed

Related Jobs

View all jobs

Associate Director of AI

Data/Artificial Intelligence Engineer (KTP Associate)

Data Science Manager

Professor - Artificial Intelligence (AI) and Digital Innovation

Senior Data Specialist

Engineering Manager - OSS and Tools

We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do Champion of Responsible AI & Data Ethics : Lead initiatives to establish and promote a culture of ethical & responsible AI use across the organisation . Develop strategies to embed ethical considerations in AI applications from design to deployment . Design and Governance of AI Ethics Framework: Create and implement a robust framework that guides AI systems' ethical development, deployment, and continuous monitoring . Ensure AI practices comply with international standards and reflect the organisation's commitment to ethical operations. AI Model Ethics Review and Audit: Establish protocols for regular ethics reviews and audits of AI models to ensure compliance with ethical standards throughout their lifecycle. Legal Liaison and Compliance Assurance: Direct collaboration with legal departments to align with the letter and spirit of the law surrounding data use, storage, and movement. This includes designing and implementing solutions that ensure compliance visibility. Training and Capacity Building: Develop and deliver training programs focused on Responsible AI principles to raise awareness and embed these practices across the organisation . Facilitate workshops and seminars to ensure ongoing learning and engagement with AI ethics. Stakeholder Engagement and Policy Advocacy: Actively engage with industry groups, regulatory bodies, and technology partners to advocate for ethical AI practices. Represent the organisation in external forums to share insights and learn from global best practices. Responsible AI Impact Assessments: Implement impact assessments for all AI projects to evaluate their ethical, social, and legal implications. Integrate these assessments into the project development process to ensure responsible implementation. Innovation in Ethical AI Practices: Sponsor research and innovation projects focused on enhancing ethical AI practices. Collaborate with academic institutions and research centres to explore new methodologies for fairness, accountability, and transparency in AI. What you'll bring 7 years of experience in Responsible AI, Data Ethics, strategy development, and execution with an u nderstanding of ethical considerations in AI and data practices. Expertise in AI Ethics and Governance: Demonstrable knowledge of the ethical issues associated with AI, such as bias, fairness, and transparency, with experience in developing or managing AI systems. Strategic Leadership and Policy Development: Proven ability to lead organizational strategy around Responsible AI, influence internal policies, and contribute to industry-wide standards. Advanced Technical Skills: Strong technical background to understand and critique complex AI and machine learning technologies, ensuring they align with ethical guidelines. Effective Communication and Advocacy: Excellent communication skills can articulate complex AI and ethical concepts to diverse audiences, from technical teams to executive boards. Collaborative and Influential Leadership: Skilled in working within matrix organisations and leading cross-functional teams. Ability to influence culture and implement change across traditional and non-traditional reporting lines. Project Management and Implementation: Strong project management skills, with experience leading large-scale projects that combine practical and cultural elements to embed Responsible AI practices in business operations. Relationship Management: Exceptional ability to manage relationships across all levels of the organisation and with external stakeholders, ensuring effective collaboration and discretion on sensitive matters. Group Data Hub Want to unlock the power of data? Our Group Data Hub works with millions of data transformations every day to deliver value, improve customer experience and enable new product launches. From architecture to analytics and engineering to science: it's how we bring customers more of what they love. The rewards There's one thing people can't stop talking about when it comes to LifeAtSky : the perks . Here's a taster: Sky Q, for the TV you love all in one place

National AI Awards 2025

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.

Part-Time Study Routes That Lead to AI Jobs: Evening Courses, Bootcamps & Online Masters

Artificial intelligence (AI) is reshaping industries at an unprecedented pace. From automating mundane tasks in finance to driving innovation in healthcare diagnostics, the demand for AI-skilled professionals is skyrocketing. In the United Kingdom alone, AI is forecast to deliver over £400 billion to the economy by 2030 and generate millions of new jobs across sectors. Yet, for many ambitious professionals, taking time away from work to upskill can feel like an impossible ask. Thankfully, part-time learning options have proliferated: evening courses, intensive bootcamps and flexible online master’s programmes empower you to learn AI while working. This comprehensive guide explores every route—from short tasters to deep-dive MScs—showcasing providers, course formats, funding options and practical tips. Whether you’re a career changer, a busy manager or a self-taught developer keen to go further, you’ll discover a pathway to fit your schedule, budget and goals.

Top 10 Mistakes Candidates Make When Applying for AI Jobs—And How to Avoid Them

Avoid the biggest pitfalls when applying for artificial intelligence jobs. Discover the top 10 mistakes AI candidates make—plus expert tips and internal resources to land your dream role. Introduction The market for AI jobs in the UK is booming. From computer-vision start-ups in Cambridge to global fintechs in London searching for machine-learning engineers, demand for artificial-intelligence talent shows no sign of slowing. But while vacancies grow, so does the competition. Recruiters tell us they reject up to 75 per cent of applications before shortlisting—often for mistakes that could have been fixed in minutes. To help you stand out, we’ve analysed thousands of recent applications posted on ArtificialIntelligenceJobs.co.uk, spoken with in-house talent teams and independent recruiters, and distilled their feedback into a definitive “top mistakes” list. Below you’ll find the ten most common errors, along with actionable fixes, keyword-rich guidance and handy internal links to deeper resources on our site. Bookmark this page before you hit “Apply”—it could be the difference between the “reject” pile and a career-defining interview.