Data & AI Product Manager — Embedded, Value-Driven

Guardrisk; Sandton; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Guardrisk is seeking a Data & AI Product Manager to own data and AI products from discovery through delivery, rollout and adoption within the Data CoE. You will partner with business teams and engineers to shape product strategy and ensure value realisation.

You will translate complex data problems into scalable data products, manage roadmaps and backlogs, and drive adoption while maintaining governance and certification standards across analytics, ML and AI initiatives.

Qualifications

• Experience leading data/analytics/AI product initiatives from discovery to production and adoption.
• Ability to map workflows, understand data lineage and trusted data foundations.
• Strong governance, certification and value-realisation focus in data products.

Responsibilities

• Own a portfolio of data and AI products within the Data CoE from discovery through live rollout.
• Shape product vision, roadmap, and backlogs aligned with business value.
• Collaborate with data engineers, data scientists and AI engineers to balance user needs and technical feasibility.
• Define requirements and acceptance criteria for data products and AI solutions.
• Drive adoption, measure usage and realised value after launch.

Skills

Data product management

Stakeholder collaboration

Product discovery

Roadmap planning

Value measurement

Technical fluency

Communication

Education

Bachelor’s degree in Business, Computer Science, Information Systems, Engineering, Data/Analytics or related

Tools

Azure DevOps

Job description

Guardrisk is seeking a Data & AI Product Manager to own data and AI products from discovery through delivery, rollout and adoption within the Data CoE. You will partner with business teams and engineers to shape product strategy and ensure value realisation.

You will translate complex data problems into scalable data products, manage roadmaps and backlogs, and drive adoption while maintaining governance and certification standards across analytics, ML and AI initiatives.