Product Manager; Data Science

At Polaris Inc., we have fun doing what we love by driving change and innovation. We empower employees to take on challenging assignments and roles with an elevated level of responsibility in our agile working environment. Our people make us who we are, and we create incredible products and experiences that empower us to THINK OUTSIDE.

You will serve as a Product Manager for Data Science, advancing enterprise Data & Analytics capabilities by delivering scalable, high-quality data products. Positioned within a centralized IT function, you will manage cross-domain data products and platforms that support analytics and decision‑making across Customer, Marketing, Supply Chain, and Finance. You will define product vision, prioritize investments, and lead delivery across the full data lifecycle to ensure data is accessible, trusted, and aligned to business outcomes.

Working in a highly cross‑functional model, you will partner with engineering, architecture, and business stakeholders while guiding execution through a distributed development team. This role offers the opportunity to drive enterprise‑wide data impact and influence how data enables strategic decision‑making at scale.

• Define and execute the product vision, strategy, and roadmap for enterprise data platforms and cross-domain data products.
• Manage and provide direction to an offshore development team of approximately 12 contractors, ensuring alignment to priorities, quality standards, and timelines.
• Prioritize investments across stakeholders using a structured, value‑driven framework aligned to business goals and Data & Analytics KPIs.
• Own the end‑to‑end lifecycle of data products, including data ingestion, transformation, modeling, and consumption.
• Ensure delivery of high‑quality, scalable, and reusable datasets and semantic models.
• Establish and manage SLAs for data availability, freshness, quality, and reliability.
• Partner with business leaders and technical teams to translate business needs into product requirements and measurable outcomes.
• Balance competing priorities across domains while maintaining focus on enterprise‑wide value.
• Lead product delivery in partnership with data engineering teams, ensuring iterative and timely value delivery.
• Maintain and prioritize the product backlog, defining clear requirements and guiding trade‑offs across scope, timeline, and technical complexity.
• Collaborate with engineering, architecture, and governance teams to support data quality, metadata consistency, security, and compliance.
• Contribute to the evolution and scalability of the enterprise data platform, including storage and integration patterns.

• Business Acumen:
  You understand how your work impacts financial performance, operational efficiency, and organizational goals, and you make decisions with the broader business context in mind.
• Collaboration:
  
  You work effectively with others across functions and levels, contributing to shared goals while respecting different perspectives.
• Data & Analytical Literacy:
  You interpret data, metrics, or reporting to inform decisions, identify trends, and measure outcomes relevant to your role.

• Bachelor’s degree in Business Analytics, Data Science, or related field.
• Minimum of 10 years of progressive experience in data & analytics.
• Minimum of 5 years of product management experience delivering digital or data‑focused products.
• Strong understanding of data ecosystems, including data warehousing, data modeling, and analytics platforms.
• Experience working with SAP data highly preferred, including understanding data structures and supporting downstream analytics use cases.
• Demonstrated success owning product roadmaps and delivering measurable business outcomes.
• Experience leading cross‑functional teams and working with distributed or offshore development resources.
• Proficiency with product management tools such as JIRA or Azure Dev Ops.
• Working knowledge of SQL and ability to engage hands‑on with data.
• Experience with modern data platforms such as Snowflake (preferred), Microsoft Fabric, Azure Synapse, or Databricks.
• Ability to work in a remote or hybrid model…