Senior Product Manager (AI, ML & Data)

ITV plc
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Product Manager - AI, ML & Data Science

Senior Machine Learning Product Manager (Deploy)

Product Manager

Senior Machine Learning Engineer

Senior Data Scientist

Machine Learning Manager

Senior Product Manager (AI, ML & Data)

CT&C

Permanent

White City, London

Hiring range: £68,000 - £75,000

Your work matters to millions.

Shaping culture is in the DNA of ITV. So, its not surprising that youll find us in every home in the UK, our productions are famous all over the world and were at the forefront of the digital streaming revolution.

When you join us, you enter a fun working environment. With opportunities to learn, to grow and make a real difference. Small enough that your impacts felt in the business, but big enough that your impact reaches millions of people.

Come develop your skills, change TV and the course of your career. Dont just watch it. Be part of it. Join ITV.

Your impact sends ripples

The role

This is an exciting opportunity to be an integral part of ITVs Commercial Technology and Change organisation. Youll be a member of the Product team, working with cross-functional teams at the forefront of defining and delivering ITVs Commercial Technology products and supporting our ambition to support our Linear and VOD inventory workflows, systems and insights. Youll have a significant influence on ITVs success in this area with strong backing and support from ITV leadership across Commercial Technology.

Key Responsibilities

Product Direction (Data)

  1. Product Strategy:Input into and articulate the strategy for AI, ML & Data focussed products and propositions for Commercial outcomes.
  2. Wider ITV Data Strategy:Ensure alignment with and promotion of wider ITV AI, ML & Data strategy.

Product Development (Data)

  1. Research & Ideation:Lead ideation around AI, ML & Data focused roadmap initiatives, and contribute new data proposition ideas.
  2. Scoping & Shaping:Direct the shaping of key AI, ML & Data focussed initiatives with creativity and judgement.
  3. Planning & Roadmap:Collaborate on the development of an outcome based roadmap that is pragmatic, innovative and business aligned. Support delivery planning with credible estimates and plans.

Product Delivery (Data)

  1. Definition:Support the definition of the data product requirements and specifications, partnering closely with other functional specialists (e.g. data analysts, data engineers, QA), suppliers and business teams to refine, clarify & prioritise.
  2. Delivery:Support the development of data products as they iterate through agile processes, driving alignment across the cross-functional team.
  3. Acceptance:Support acceptance processes, ensuring alignment with the original specifications and focusing on data quality.

Operate & Run (Data)

  1. Transition:Provide guidance and expertise to the transition of product developments into smooth operational running, including with business teams.
  2. Support:Respond to inbound support queries around data products, and identify potential product iterations resulting from those interactions.
  3. Improvement:Define data product improvements through ideation and understanding of data product performance and adoption.

Other things were looking for(key criteria)

  1. Ability to explain complex concepts in a clear and simple manner, particularly around AI, ML & data focused concepts.
  2. Well reasoned communication.
  3. Data querying skills required (SQL or equivalent), with additional coding knowledge if possible (e.g. Python).
  4. Strong understanding of big data processing frameworks (e.g. PySpark), analytics and data visualisation tools, data experimentation techniques, ML & data science methodologies (e.g. large language models, GenAI, ML models), decentralised and medallion data architectures.
  5. Keen but pragmatic problem solver who is able to demonstrate justifiable logic and curiosity and open-mindedness in data-led innovation.
  6. Excellent attention to detail.
  7. Robust understanding of AI, ML and data landscape and trends.
  8. Awareness of operating data products within a data governance framework, with data privacy principles, and ensuring cyber security and data quality.

ITV is for everyone.

ITV strongly encourages applications for this role from disabled people. As a Disability Confident Leader, if you meet the minimum criteria for a role and you have declared that you are disabled, well guarantee to take you to the next stage*(minimum criteria above).

Were happy to discuss any support/personalisation you may need during our application and selection process as part of our reasonable adjustments. Drop us a line if you require anything at .

Find out moreabout applying with a disability.

* There may be a few exceptions where we are not able to take all eligible candidates to the next stage due to the volume of applications.

Because those who make an impact deserve to be rewarded for it.

ITV offers some great rewards and benefits including:

  1. Flexible working with a range of options
  2. Generous holiday allowance, plus you can buy more
  3. Annual bonus opportunity
  4. Competitive pension contribution
  5. Save as you earn - with an opportunity to buy ITV shares
  6. Wellbeing and volunteering days plus a wide range of opportunities to help you live a balanced and healthy life

Closing date: Friday 21st March 2025J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.