Product Manager

KPI Partners is seeking a driven and innovative Product Manager specializing in AI/ML and Analytics to join our dynamic team. In this role, you will be responsible for defining the product vision, strategy, and roadmap for our analytics solutions that leverage artificial intelligence and machine learning technologies. 

Key Responsibilities: 
• Define and own the product vision, strategy, and roadmap for enterprise data, analytics, and AI platforms.

• Partner with business, engineering, data science, and architecture teams to prioritize high-impact use cases.
• Lead cross-functional coordination across data engineering, analytics, AI/ML, security, and business teams.
• Lead execution of initiatives, ensuring on-time delivery within scope, quality, and budget expectations.
• Manage dependencies, risks, and issue resolution across multiple workstreams and stakeholders.
• Ensure alignment with enterprise architecture, data governance, security, and compliance frameworks.
• Drive adoption of enterprise data platforms, analytics solutions, and AI/ML capabilities.
• Define and track product KPIs including adoption, usage, performance, data quality, and business value realization.
• Lead stakeholder engagement and executive communication, translating technical concepts into business value.
• Drive change management and enablement, including onboarding, training, and rollout strategies.
• Partner with engineering teams to optimize cost, performance, scalability, and reliability of solutions.
• Drive license governance and optimization, including entitlement strategy, usage monitoring, cost management, and ROI realization.

Required Qualifications

• Bachelors degree in engineering, Computer Science, Information Systems, or a related field
• 10+ years of experience in program management, product management, or delivery leadership in:
• Data Engineering
• Analytics platforms
• AI / ML or advanced analytics solutions
• Proven experience managing complex, crossfunctional, enterprisescale programs
• Strong understanding of:
• Software Development Life Cycle (SDLC)
• Architecture governance and review processes
• Data, analytics, and AI ecosystems