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WHOOP

Senior Manager, Commercial Analytics

Posted 4 Days Ago
Be an Early Applicant
Hybrid
Boston, MA
170K-200K Annually
Senior level
Hybrid
Boston, MA
170K-200K Annually
Senior level
Leads commercial analytics across digital commerce, apparel and accessories, and wholesale. Manages analysts, owns bookings forecasting, develops customer and channel economics frameworks, and builds scenario-planning and measurement models. Partners with Finance and senior stakeholders to evaluate growth opportunities, diagnose performance, quantify tradeoffs, and guide investment decisions. Requires strong SQL, analytical modeling, people leadership, and cross-functional business judgment.
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At WHOOP, we're on a mission to unlock and inspire performance for life.

WHOOP is hiring a Senior Manager, Commercial Analytics to support our commercial business across sales channels. In this role, you will oversee reporting to understand commercial performance, evaluate growth opportunities, and make informed investment decisions.

You will lead a team of analysts supporting Digital Commerce, Apparel & Accessories, and Wholesale while remaining hands-on with the highest-impact analytical work. You will partner closely within the broader analytics team and across the organization to translate complex data into clear business decisions and establish consistent measurement across the commercial organization.

RESPONSIBILITIES:
  • Lead and develop a team of analysts supporting Digital Commerce, Apparel & Accessories, and Wholesale, setting clear priorities and ensuring analytical work translates into meaningful commercial impact.

  • Own the commercial bookings model and short-term, bottoms-up forecasting, explaining performance across channels, geographies, products, and partners and partnering with Finance to reconcile channel-level forecasts with company planning.

  • Establish consistent frameworks for evaluating channel and customer economics to enable informed comparisons and investment decisions across the commercial organization.

  • Build scenario-planning and measurement frameworks that quantify tradeoffs across volume, cost, retention, pricing, mix and margin.

  • Run point on critical commercial decisions and operating rhythms, diagnose the drivers of bookings and member economics, and translate findings into clear recommendations for senior stakeholders.

  • Partner cross-functionally to improve the data, measurement, and analytical capabilities that support commercial decision-making.

QUALIFICATIONS:
  • Bachelor's or advanced degree in Business, Economics, Math, Statistics, Data Science, or a related field.

  • 7+ years of experience in analytics, data science, strategic finance, commercial strategy, or a related discipline, with demonstrated experience using customer and unit economics to inform business decisions.

  • Experience building or owning commercial measurement frameworks such as LTV, CAC, payback, contribution margin, forecasting, scenario planning, or incrementality, ideally within a subscription, recurring-revenue, or multi-channel business.

  • Demonstrated people leadership experience, with a track record of developing talent, setting priorities, and maintaining high standards for analytical quality and business impact.

  • Strong SQL skills and experience working with modern data infrastructure, paired with proficiency in Python, R, or comparable analytical tools for modeling and advanced analysis.

  • Experience partnering with senior commercial, sales, marketing, or finance stakeholders to frame ambiguous business questions, evaluate tradeoffs, and translate analysis into clear recommendations and actions.

  • Strong business acumen and understanding of analytical measurement, including the ability to evaluate modeling approaches and their limitations and effectively partner with Data Science and other technical teams.

  • Experience working in omni-channel businesses and establishing shared metrics or analytical standards across teams is a plus.

  • 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.

    This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.

     

    Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.

    WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility

    The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.

    At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.

    The U.S. base salary range for this full-time position is $170,000 - $200,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.

    In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.

    These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

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