Product Manager, Data & Analytics

About the Role

Nature's Sunshine is entering an ambitious new phase of growth, and data will play a central role in how the company scales. As part of that investment, we are building a new Enterprise Data & Analytics function to unlock trusted data, sharpen decision-making, and help teams improve business performance.

We are looking for a Product Manager to turn business needs into a focused roadmap for analytics products, reporting experiences, KPI adoption, and decision-support capabilities.

This is an analytics product role, not project coordination or report delivery. You will own the why, what, and priority of analytics products while partnering with analytics engineers, BI developers, business leaders, IT, and data governance stakeholders.

• Own the analytics product roadmap for assigned business domains or enterprise priorities.
• Lead intake, discovery, scoping, and prioritization for analytics requests, dashboards, reporting products, and decision-support tools.
• Make tradeoff recommendations based on business value, urgency, effort, reusability, adoption likelihood, and strategic priority.
• Translate unclear needs into problem statements, requirements, user stories, acceptance criteria, and success measures.
• Own backlog artifacts in Azure Dev Ops, including epics, features, user stories, dependencies, and prioritization context.
• Partner with business leaders to clarify decision needs, reporting gaps, KPI ownership, and metric definitions.
• Partner with Data Engineering, Analytics Engineering, and BI Development to translate business priorities into reliable data pipelines, governed metrics, semantic models, reusable data assets, and usable reporting experiences.
• Track adoption, usage, satisfaction, and business impact; reduce duplicate reporting and low-value one-off work.

• 4+ years of experience in product management, analytics product ownership, business analysis, BI delivery, consulting, or a related role.
• Proven ability to translate business problems into clear analytics requirements and prioritized delivery plans.
• Experience working with BI tools, reporting products, KPIs, analytics products, or enterprise data platforms.
• Strong stakeholder management skills across business, technical, and leadership audiences.
• Ability to separate the stated request from the underlying business problem and right analytics solution.
• Sound prioritization judgment across value, urgency, complexity, reusability, and strategic fit.
• Clear written and verbal communication; comfort operating through ambiguity and competing priorities.
• Ability to partner with technical teams without personally owning data engineering, semantic modeling, or dashboard development.

• Experience with Power BI, Microsoft Fabric, Azure, Snowflake, Databricks, Tableau, Looker, or similar platforms.
• Experience managing analytics roadmaps, BI backlogs, data product portfolios, or reporting governance processes.
• Experience using Azure Dev Ops or a similar tool to manage epics, features, user stories, and acceptance criteria.
• Experience communicating roadmap decisions, tradeoffs, and delivery status to senior stakeholders.
• Familiarity with data governance, KPI standardization, semantic models, certified datasets, or enterprise reporting standards.
• Interest in using AI-assisted workflows to improve discovery, documentation, backlog refinement, stakeholder communication, and product management practices.

You will thrive in this role if you like turning messy business needs into clear choices, asking sharp questions, and focusing teams on analytics work that improves decisions.

You should be able to challenge assumptions, redirect low-value requests, and say not yet or not that way with credibility and tact. You do not need to be the deepest technical expert in the room, but you do need enough analytics fluency to understand tradeoffs, dependencies, data quality risks, and adoption barriers.

• Roadmap priorities are clear, visible, and aligned to business needs.
• Intake and prioritization decisions are transparent and defensible.
• Analytics products have clear users, owners, success criteria, and lifecycle status.
• Adoption, usage, and satisfaction improve for priority analytics products.
• Duplicate, low-value, or poorly defined reporting requests decrease over time.