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.
Content Technology & Innovation is accelerating the responsible use of artificial intelligence across content operations, production workflows and business processes.
The AI Product Analyst will work closely with the Senior AI Product Manager and Innovation AI Engineers to identify customer problems, shape product opportunities and turn emerging AI capabilities into valuable products and services.
The role will work directly with customers and stakeholders to understand needs, define experiments, evaluate results and help determine what should progress from exploration through prototype, pilot and production.
A key part of the role will also be establishing consistent approaches to benchmarking AI products, models and vendors, ensuring product decisions are supported by clear evidence.
This role sits at the intersection of product, AI, engineering, experimentation and business strategy.
What you'll do:
Product management and customer engagement
Work with the Senior AI Product Manager to develop and deliver MIAS and wider Content AI product priorities.
Engage directly with customers to understand problems, workflows and opportunities.
Translate customer needs into clear use cases, requirements, hypotheses and success criteria.
Support prioritisation of opportunities based on customer value, technical feasibility, cost and risk.
Maintain strong customer feedback loops throughout experiments, prototypes and pilots.
Represent MIAS and our wider Content AI strategy in stakeholder conversations.
Experimentation and engineering collaboration
Work alongside Innovation AI Engineers to plan and execute AI experiments, prototypes and proofs of concept.
Define experiment objectives, success measures and evaluation approaches.
Coordinate activity between customers, product and engineering teams.
Review outputs with customers and subject matter experts and identify opportunities for improvement.
Turn findings into clear recommendations for product and engineering priorities.
Identify reusable capabilities that can become part of MIAS rather than remain one-off solutions.
AI evaluation and benchmarking
Design and run repeatable evaluation frameworks for AI products, models and vendors.
Build and maintain representative benchmark datasets aligned to real business use cases.
Work with subject matter experts to establish appropriate ground truth.
Assess quality, accuracy, reliability, consistency, latency, cost and business value.
Use appropriate measures such as precision, recall, error rates and human agreement.
Identify failure modes and trade-offs and use these to inform product improvement.
Compare competing AI solutions against common criteria and test vendor claims through practical evidence.
Insight, communication and representation
Translate complex technical findings into clear recommendations for technical and non-technical audiences.
Present experiments, product strategy and recommendations to senior stakeholders.
Support product demonstrations, showcases and customer workshops.
Maintain clear documentation covering decisions, assumptions, results and recommendations.
Partner across product, innovation, engineering, operations, commercial and governance teams.
Essential Criteria:
Ability to translate business needs into clear product opportunities, experiments and success criteria
Comfortable working in an experimental environment where requirements and solutions evolve quickly
Ability to analyse qualitative and quantitative results and communicate uncertainty
Confident working directly with customers, engineers, subject…