Business Analytics Senior Manager (Product)

Responsibilities

• Partner with Product, Software, Hardware, Algorithms, and UX teams to align on goals, quantify impact, and identify new sources of value for WHOOP members.
• Serve as the primary analytics partner across algorithms, core product, and hardware product workstreams, adapting your approach to the unique needs of each domain.
• Lead, manage, and develop a team of analysts by fostering a culture of high performance, intellectual rigor, and continuous improvement. Invest in career development and raise the analytical bar across the organization.
• Create repeatable tools and processes for analytics at scale, from data pipelines to agentic reporting solutions to weekly performance reviews.
• Generate and drive a strategic analytic roadmap that proactively surfaces insights about member behavior, product performance, and feature adoption.
• Build and refine KPIs across product domains including engagement, retention, feature adoption, and hardware performance metrics.
• Design and oversee experimentation (A/B testing, causal inference) with clear success criteria, and bring rigor to how we measure what's working and what isn't.
• Collaborate with machine learning & research teams to evaluate model outputs, challenge assumptions, and ensure algorithmic work translates effectively into the product experience.
• Provide thought leadership to senior stakeholders, delivering action-oriented recommendations that influence product roadmaps and strategic direction.

Qualifications

• 8+ years of experience in a deeply strategic/analytical role, including partnership with product and development teams.
• Direct experience leading and developing a team of analysts, including driving large cross-functional projects and mentoring junior team members.
• A true player-coach — able to independently take broad business questions, wrangle appropriate data, isolate and model key insights, visualize results, and communicate actionable recommendations.
• Strong storytelling skills — able to create compelling, concise presentations that convey actionable solutions to complex, ambiguous problems.
• Demonstrated success influencing senior stakeholders and leadership on strategic direction based on analytical recommendations.
• Experience and knowledge running experiments (e.g., A/B testing, causal inference) and working with development teams.
• Comfortable immersing yourself in new contexts — able to engage with technical PMs and data scientists on topics like data quality, device-level analytics, and signal processing tradeoffs enough to be a credible thought partner.
• Experience working across multiple product domains simultaneously is strongly preferred.
• Advanced skills in SQL and understanding of ELT (dbt) and data warehousing (Snowflake) structures, as well as data visualization tools (e.g., Looker, Hex, Tableau).
• Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions.