Key Responsibilities
AI & Data Product Management
- Own the full lifecycle of AI and data products, from discovery, use case definition, implementation, go-live, to performance measurement.
- Collaborate closely with stakeholders (HR, Finance, Accounting, IT, Leadership) to identify suitable problems for AI or data-driven solutions, clarify expected value, success criteria, and constraints.
- Define product vision, roadmap, and backlog for AI initiatives, balancing experimentation, feasibility, and business impact.
- Work directly with AI Engineers, Software Engineers, Data Analysts, and Solution Architects to translate business requirements into clear product specifications and prioritized implementation plans.
- Validate AI use cases through PoCs and prototypes, ensuring solutions are practical, explainable, and aligned with governance, security, and data availability requirements.
- Measure and communicate AI product effectiveness by tracking adoption, performance, and business impact.
Business Intelligence & Reporting
- Act as Product Owner for BI assets, including dashboards, reports, and KPI systems used across functional departments.
- Define and maintain KPIs, metric definitions, and reporting logic to ensure consistency, accuracy, and alignment with business needs.
- Manage the BI backlog, prioritizing dashboard enhancements, new reporting requirements, and data upgrades based on stakeholder value.
- Collaborate with Data Analysts and Engineers to ensure ETL pipelines, data models, and visualizations support stable and scalable reporting needs.
- Review and validate dashboards on Tableau and Power BI to ensure clarity, usability, and effective decision support.
- Drive BI product adoption by guiding users on proper usage and ensuring clear understanding of data limitations and dashboard constraints.
Requirements
- Bachelor's degree in Information Systems, Computer Science, Data Science, or a related field.
- 35 years of experience in Product Management, Data Product, BI Product, or data-related roles.
- Experience working closely with business stakeholders, with the ability to translate ambiguous problems into concrete product requirements and measurable outcomes.
- Strong data foundation, including understanding of ETL concepts, data modeling, and how data flows from source systems to dashboards/reports.
- Hands-on experience with data visualization tools such as Tableau and/or Power BI, with the ability to review and challenge dashboard logic and design.
- Understanding of AI and Machine Learning concepts, including LLM-based use cases and applied AI workflows (no deep research background required).
- Experience using low-code/no-code tools to prototype AI workflows, dashboards, or AI-enabled processes.
- Ability to work effectively with engineers and system architects, understanding technical trade-offs without necessarily writing production code.
- Strong prioritization, communication, and stakeholder management skills, especially in business-driven environments.
- Structured, practical mindset focused on building usable products that create real value rather than merely experimenting with technology.
