Data Product Manager

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Define and drive product vision, strategy, and execution for AI-driven user enablement, spanning natural language insights, analytics experiences, developer productivity tools, and enterprise chatbots.
Partner with engineering, data science, and platform teams to deliver scalable and secure solutions across cloud and enterprise ecosystems.
Lead user discovery and research across multiple personas (business associates, plant engineers, analysts, developers) to ensure solutions address real pain points.
Translate user needs into epics, PRDs, and evaluation benchmarks; prioritize features and enhancements using impact-driven frameworks.
Build and maintain success metrics around adoption, accuracy, usability, and performance to guide continuous improvement.
Advocate for governance, metadata quality, and knowledge management to ensure AI-driven tools produce accurate and trusted results.
Communicate product strategy and progress to senior leadership and stakeholders, influencing adoption and organizational alignment.

User Adoption: Measurable growth in unique active users across business and developer personas.
Accuracy & Trust: ≥ 80% accuracy on benchmarked AI responses, with high user satisfaction scores.
Productivity Impact: Demonstrable improvements in developer and analyst productivity through AI-driven automation and insights.
Scalability: New teams/domains onboarded with reduced friction and improved metadata quality.

8–10 years of Product Management experience, ideally with data, analytics, AI/ML, or developer tools.
Proven success in AI/ML-enabled products, with strong understanding of large language models (LLMs), NLP, and conversational interfaces.
Strong grasp of cloud technologies, enterprise data platforms, and modern analytics ecosystems.
Demonstrated ability to work across cross-functional teams (engineering, ML, UX, business stakeholders) to drive end-to-end delivery.
Excellent skills in user research, stakeholder engagement, and storytelling with data.
Experience setting KPIs and evaluation frameworks for AI/analytics products.
Strong written and verbal communication skills; able to engage both executive and technical audiences.

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