AI Product Strategist II

AI Product Strategist II

The AI Product Strategist II is an individual contributor role. This role will play a critical role in Niagara’s data-driven transformation by supporting value-focused analytics products and delivering actionable insights. The role will collaborate closely with cross-functional teams to analyze business data, identify use cases, develop business cases, design solutions, optimize decision-making, and contribute to the seamless integration of analytics products into operations.

• Own the lifecycle of analytics products, including inception, development, maintenance, documentation, and enhancements focused on Sales & Marketing.
• Partner with business stakeholders to gather requirements and translate them into analytical solutions.
• Lead detailed data analysis to identify trends, patterns, and opportunities for business improvement.
• Generate and present insights to stakeholders to enhance decision-making and operational efficiencies.
• Lead or assist in Design Thinking & Hackathon workshops to support problem-solving, prioritization, and idea generation for analytics initiatives.
• Collaborate with the Enterprise Data Foundation and Data Science teams to implement analytics solutions effectively.
• Apply Agile methodologies in delivering Minimum Viable Products and iteratively scaling solutions for business value.
• Utilize data visualization tools (e.g., Power BI) to translate complex data into clear and actionable visualization of insights.
• Maintain and prioritize analytics initiatives in collaboration with the team, ensuring alignment with business objectives.
• Coach and train junior analysts and lead knowledge-sharing initiatives to enhance data literacy within the organization.
• Continuously monitor and evaluate the effectiveness of analytics solutions, identifying areas for improvement. Provide insights to support Lean Manufacturing, Six Sigma, and Continuous Improvement (CI) initiatives using data-driven analysis.
• Partner with Data Science to operationalize predictive and prescriptive models for maintenance, quality, and throughput optimization.
• Experience working with OEE, FPY, downtime analysis, scrap and rework data, and predictive maintenance programs.
• Prioritize and manage the analytics product roadmap, ensuring solutions align with business goals and operational efficiency targets.
• Strong understanding of manufacturing processes, production systems, and equipment performance metrics.
• Deep appreciation of shop-floor realities, enabling effective translation of operational challenges into data and technology solutions.

Minimum Qualifications:

• 2 years of experience in Technology Consulting or Data Analytics.
• 2 years of experience in or supporting Operations/Strategy.
• 2 years of experience managing projects.
• 2+ Years of experience in Field or a similar manufacturing environment.

Preferred Qualifications:

• 4 years of experience in Technology Consulting or Data Analytics.
• 4 years of experience in or supporting Operations/Strategy.
• 4 years of experience managing projects.
• 4 Years of experience in Field or a similar manufacturing environment.

• Business & Process Understanding:
  Deep comprehension of business processes, functional digital capabilities (Supply Chain, Manufacturing, Finance, Sales & Marketing), and high-quality analytics delivery.
• Product & Project Management:
  Skilled in managing roadmaps, backlog prioritization, release planning, sprint metrics, and cross-team coordination while ensuring business value-driven outcomes.
• Strategic Alignment & Decision Support:
  Ensures analytics products and strategies align with organizational goals, driving informed decision-making.
• User-Centric Approach:
  Deep understanding of customer journeys, UX/UI principles, and empathy-driven engagement to create impactful analytics products.
• Business Agility & Problem-Solving:
  Think-big, fail-fast mindset with strong analytical and problem-solving skills to identify root causes and drive effective solutions.
• Effective Communication of Insights:
  Translate complex data findings into understandable and actionable insights for both technical and non-technical stakeholders, using…