Product Manager (NRF)

 

Industry/ Organization Type: Information Technology Consulting

Position Title: Product Manager (Esp Data & AI Platform)

Working Location: Pasir Panjang

Working Hours: 5 days, Mon – Fri (8:30 AM – 6:00 PM, Fri 8:30 AM - 5:30 PM)

Salary Package: Basic Salary + Completion Bonus

Duration: 1 year contract (renewable)

 

Key Responsibilities

Define and communicate the product vision and strategy for the enterprise data hub, aligned with user needs and business goals.

Manage the data hub as a product platform, balancing the needs of data producers, users, analytics, and AI use cases.

Conduct user research, interviews, and testing, and analyse data and feedback to identify problems and guide product decisions.

Translate product strategy into clear requirements, user stories, and acceptance criteria.

Identify and manage risks across the product lifecycle, including data, security, AI, and operations.

Prioritise and maintain the product backlog to deliver high-impact data and AI features.

Collaborate with engineering, design, project teams, data owners, and policy teams, and communicate updates to stakeholders.

Plan and support product launches, monitor performance, and improve based on results.

Define success metrics, data requirements, and reporting methods to track outcomes.

Work with data owners to ensure data quality, governance, access control, and proper usage.

Identify and assess AI opportunities, evaluate feasibility and risks, and translate them into clear use cases.

Ensure AI features are practical for daily use, including monitoring performance and supporting adoption through training and communication.

Any ad hoc duties assigned

 

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Minimum 7 years of experience in product management.

Strong analytical skills and ability to use data for decision-making.

Experience working with cross-functional teams and aligning stakeholders.

Experience managing product lifecycle and go-to-market activities.

Good technical understanding to work with engineering teams on requirements and constraints.

Strong communication and stakeholder management skills.

Experience with data platforms (e.g. data lakes, warehouses, APIs, pipelines).

Experience with data or AI-related products, including understanding risks and implementation.