Sr. AI Product Strategist

Niagara Bottling•Diamond Bar, CA

2d•$100,464 - $145,673

About The Position

The Sr. AI Product Strategist will play a critical role in Niagara’s data-driven transformation by supporting value-focused analytics products and delivering actionable insights. This role will collaborate closely with cross-functional teams to analyze business data, optimize decision-making, and contribute to the seamless integration of analytics into operations. Analytics Product Management & Insights, as part of the larger Data and Decision Intelligence team, is pivotal in defining the future of Niagara’s decision-making framework, ensuring a competitive advantage across various business functions such as Supply Chain, Manufacturing, Finance, and Sales & Marketing.

Requirements

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
experience may include a combination of work experience and education
Bachelor's Degree in Supply Chain/Information Technology/Business Analytics/Systems Engineering/Data Science or other related field

Nice To Haves

6 years of experience in Technology Consulting or Data Analytics
6 years of experience in or supporting Operations/Strategy
6 years of experience managing projects
experience may include a combination of work experience and education
Master's Degree in Supply Chain/Information Technology/Business Analytics/Systems Engineering/Data Science or other related field
APICS CPIM/CSCP, PMP PMI

Responsibilities

Support the lifecycle of analytics products, including inception, development, maintenance, documentation, and enhancements.
Partner with business stakeholders to gather requirements and translate them into analytical solutions.
Conduct 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.
Assist in Design Thinking 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 intuitive and actionable dashboards.
Maintain and prioritize analytics initiatives in collaboration with the team, ensuring alignment with business objectives.
Support training and knowledge-sharing initiatives to enhance data literacy within the organization.
Continuously monitor and evaluate the effectiveness of analytics solutions, identifying areas for improvement.