Product Analyst

NMDP•Minneapolis, MN

About The Position

The Product Analyst plays a critical role in enabling product teams to make data-informed decisions by translating complex data into actionable insights. Embedded within the product organization, this role partners closely with Product Managers, Product Owners, and Decision Support to assess product performance, evaluate opportunities, and support prioritization across the product lifecycle. The Product Analyst focuses on understanding product outcomes, customer and stakeholder needs, and operational performance—helping ensure that product investments align with organizational strategy and deliver measurable value.

Requirements

Knowledge of Product analytics and performance measurement, including defining, tracking, and interpreting product level metrics and outcomes.
Knowledge of Data informed decision making, using quantitative and qualitative insights to evaluate options, assess impact, and guide product and business decisions.
Knowledge of Translating business and product questions into analytical approaches, ensuring insights are actionable and decision oriented.
Knowledge of Outcome based measurement and value assessment, supporting prioritization and investment decisions across the product lifecycle.
Knowledge of Decision support and insight storytelling practices, effectively communicating findings to technical and non technical stakeholders.
Ability to collaborate effectively with cross-functional partners, including product, technology, and analytics teams.
Strong analytical thinking and problem-solving skills, with the ability to synthesize complex information into clear narratives.
Comfort operating in ambiguity and evolving organizational models.
Ability to think strategically, connecting data and insights to broader organizational goals, product outcomes, and long-term value.
Ability to communicate clearly and concisely, translating complex analytical findings into actionable insights for both technical and non-technical stakeholders.
Ability to collaborate and influence effectively across cross-functional teams, building strong partnerships and supporting data-informed decision making.
Bachelor’s degree in analytics, business, economics, information systems, or a related field, or equivalent professional experience.
3-5 years experience analyzing data and translating insights into business or product recommendations.
Experience working in or alongside a product-oriented organization.
Familiarity with product metrics, outcome-based measurement, or portfolio-level analysis.
Experience supporting strategic or decision-support initiatives within a matrixed organization.

Nice To Haves

Use of artificial intelligence within research, aggregation and scenario planning.

Responsibilities

Analyze product performance, usage, and outcomes to generate insights that inform product strategy, roadmap decisions, and prioritization.
Analyze user behavior, adoption trends, performance metrics and customer feedback.
Develop and maintain product-level metrics, dashboards, and reporting in partnership with Decision Support and analytics teams.
Translate data into clear insights and recommendations for Product and leadership teams.
Support hypothesis testing, opportunity sizing, and impact assessment for new and existing product initiatives.
Partner closely with Product Managers and Product Owners to understand business objectives, customer problems, and desired outcomes.
Translate business questions into analytical approaches and clearly communicate findings to both technical and non-technical audiences.
Support trade-off discussions by providing data-backed insights on value, risk, and impact.
Collaborate with Decision Support and Market Research functions to ensure consistency in insights, metrics, and storytelling across the product portfolio.
Contribute to product reviews, planning sessions, and governance discussions by bringing forward relevant data and insights.
Help standardize analytical practices and tools used across product teams as the organization matures in its product model.
Track benefit realization and adoption post-implementation.
Identify opportunities for optimization based on performance data.
Recommend improvements based on data and user feedback.
Support regular product review cadences with performance reporting.