Data Product Manager | AI | Inhouse
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High-Impact AI & Data Initiatives: Opportunity to own end-to-end strategy and directly shape next-generation enterprise data, analytics, and AI/ML products rather than just managing incremental software updates.
Join an established, forward-thinking global brand known for engineering excellence and rapid adoption of emerging technologies.
About the company
Our Client is an established company. With rapid expansion plan, they are now looking for a Data Product Manager to join their team.
About the job
Reporting directly to the Head of SAP based in Europe, Your role involves:
Define and execute strategic product roadmaps for enterprise data, reporting, and AI/ML solutions.
Engage with cross-functional stakeholders to gather business needs and translate them into technical features.
Direct delivery teams through feature prioritization, backlog management, and resource alignment.
Partner with Data Operations to track solution performance, resolve operational issues, and maintain system health.
Establish post-deployment adoption metrics to evaluate business value, usage, and opportunities for continuous iteration.
Lead change management, end-user training, and compliance alignment across security, privacy, and architecture frameworks.
Skills and experience required
As a successful applicant, you will have at least 7 years of managing technical data products, business intelligence platforms, or AI/ML solutions.
Industry background from manufacturing, engineering and FMCG will be of added advantage.
Whats on offer
This is an excellent opportunity to join an established company with strong pipeline of projects and high investment in technology.
To apply online please use the 'apply' function, alternatively you can reach me at https://www.linkedin.com/in/hoonteck-nologyrecruitment. (EA: 94C3609/ R1219669)
Desired Skills and Experience
Data Products, Product Management, Artificial Intelligence (AI), python, machine learning, data science, Data analysis, natural language processing (NLP), PySpark