Product Manager

Key Responsibilities:

• Define and communicate a clear product vision and strategy for the organisation's enterprise data hub, aligned with user needs and organisational goals.
• Own the data hub as a product platform, balancing the needs of data producers, data consumers, analytics, and AI-enabled use cases.
•  Lead user research, customer interviews, and usability testing to identify core problems, unmet needs, and opportunities for data- and AI-enabled improvements.
• Analyze quantitative and qualitative data to guide product decisions and measure success.
• Translate product strategy into detailed requirements, user stories, and acceptance criteria.
• Identify potential risks across the product lifecycle, including data, security, AI, and operational risks; implement mitigation measures and maintain the risk register.
• Priorities and maintain the product backlog to ensure delivery of high-impact data and AI capabilities.
• Collaborate closely with engineering, design, project management, data owners, and policy teams across directorates.
• Communicate product roadmap updates and manage expectations with senior leadership and stakeholders.
• Plan and execute product launches; monitor post-launch performance and iterate based on outcomes.
• Define what success looks like for the product, including key metrics, data requirements, and reporting/insight mechanisms to track outcomes.
• Partner with data owners to ensure data quality, governance, access controls, and appropriate use of data across the product lifecycle.
• Identify and validate AI opportunities (e.g. automation, decision support, summarization, triage) through structured discovery, and translate them into clear use cases, success measures, and incremental deliveries.
• Assess AI feasibility and risks, including data readiness, integration constraints, model limitations, ethical considerations, and operational support requirements.
• Ensure AI-enabled features are operationally viable, including model lifecycle management, human-in-the-loop controls, monitoring of performance and risks, and integration into day-to-day workflows.
• Drive adoption and change enablement for data and AI features (training, communications, stakeholder alignment), ensuring they genuinely extend workforce capacity and improve decision quality.

Qualifications:

• Minimum 5 years of experience in product management.
• Strong analytical and product sense, with experience using data to make decisions.
• Proven ability to manage cross-functional teams and drive alignment across multiple directorates.
• Experience with go-to-market strategy and end-to-end product lifecycle management.
• Strong technical fluency to engage engineering teams on feasibility, constraints, and trade-offs.
• Strong communication and stakeholder management skills, including engagement with senior leadership.
• Hands-on experience working with data platforms (e.g. data lakes, warehouses, APIs, pipelines) and AI-enabled systems, with sufficient depth to challenge assumptions and make informed product decisions.
• Experience delivering or managing data- or AI-enabled products, including understanding feasibility, risks, operational considerations, and change management