At a Glance
- Tasks: Lead the Data & AI product backlog and deliver innovative AI-enabled solutions.
- Company: Join a respected global organisation focused on digital transformation and technology.
- Benefits: Earn up to £90,000 with bonuses, pension contributions, and flexible working options.
- Other info: Enjoy extensive learning opportunities and clear career progression pathways.
- Why this job: Drive meaningful change in AI while collaborating with a forward-thinking tech team.
- Qualifications: 3+ years as a Product Owner in Data, AI, or Digital Products.
The predicted salary is between 90000 - 90000 £ per year.
Product Owner (Data & AI) / AI Product Manager - London (Hybrid)
Generative AI - Data & Analytics - Power BI - Agile - Digital Transformation - up to £90,000
We’re partnering with a highly respected global organisation investing heavily in its Data & AI capabilities as part of an ambitious digital transformation programme. This is an opportunity to join a business where technology is a strategic priority, giving you the chance to influence how AI, automation and data products are adopted across an international operation. You’ll be joining a collaborative, forward‑thinking technology team delivering innovative solutions that improve decision‑making, operational efficiency and business performance.
If you’re passionate about AI and enjoy turning business challenges into scalable technology solutions, this role offers a fantastic opportunity to drive meaningful change while working with some of the latest developments in Generative AI, AI Agents and intelligent automation.
Responsibilities
- Own, prioritise the Data & AI product backlog.
- Translate requirements into epics, user stories, acceptance criteria.
- Partner with stakeholders across multiple regions.
- Deliver AI‑enabled products including GenAI, AI Agents, NLP, automation, analytics.
- Shape AI use cases from concept through delivery.
- Define requirements, data readiness, evaluation criteria, operational needs.
- Drive data quality, governance, lineage, accessibility.
- Support experimentation, innovation, continuous improvement.
- Work within Agile Scrum, Kanban environments.
Benefits
- Salary up to £90,000.
- Discretionary annual bonus.
- 8% employer pension contribution.
- Enhanced parental leave.
- Extensive learning and development opportunities.
- Clear career progression pathways.
- Flexible and hybrid working arrangements.
Key Experience
- 3+ years Product Owner experience within Data, AI, Analytics, BI, Automation, Digital Products.
- Proven backlog ownership delivering measurable outcomes.
- Strong Business Analysis skills including workshops, requirements gathering, process mapping, user stories, acceptance criteria.
- End‑to‑end delivery experience across data, analytics, automation, digital products.
- Knowledge of Generative AI, AI Agents, Machine Learning, NLP.
- Experience defining AI requirements, success measures.
- Power BI experience within governed reporting environments.
- Understanding of data modelling, metrics, lineage, self‑service analytics.
- Knowledge of GDPR, governance, risk, security frameworks.
- Agile delivery experience (Scrum, Kanban).
- Strong stakeholder management, communication skills.
Product Owner (Data & AI) / AI Product Manager in London employer: Cyber Security training courses
As an AI Engineer at our Central London office, you will be part of a dynamic team dedicated to pioneering cutting-edge AI solutions that drive business growth and enhance engineering capabilities. We pride ourselves on fostering a collaborative work culture that encourages innovation and professional development, offering competitive salaries, performance bonuses, and the flexibility of a hybrid working model to ensure a healthy work-life balance.
Contact Details:
Cyber Security training courses Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Product Owner (Data & AI) / AI Product Manager in London
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We think you need these skills to ace Product Owner (Data & AI) / AI Product Manager in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cyber Security training courses. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cyber Security training courses
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cyber Security training courses!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
