We're looking for a Business Analystto embed with our Operations team, specifically supporting the Manufacturing & Quality streams by helping bridge the gap between operational processes and data. This role will be instrumental in building out quality analytics capabilities across the product lifecycle, from production through field performance. You'll own key quality metrics, develop new reporting, build new tools, and partner with manufacturing and field quality engineers to turn operational data into decisions.

This is a high-impact role for someone who is able to successfully use analytical skills to target operational challenges and drive continuous improvement.

RESPONSIBILITIES

• Partner with Field Quality, Manufacturing, and Reliability Engineering teams to define and monitor product quality KPIs across the supply chain
• Own quality metrics reporting on production yields, field failure rates, supplier quality indicators to proactively surface trends related to product build and performance
• Develop and maintain reporting and self-service analytics tooling for operations stakeholders
• Support ad-hoc analyses for test result validation, issue containment & impact sizing, failure mode investigations, cost quantification
• Collaborate with Data Platform and Analytics Engineering to land new relevant quality data sources in Snowflake and build them into usable models
• Help define data capture standards for new processes (e.g., incoming inspection, NPI qualification, supplier data) where structured data doesn't exist today
• Translate between technical data requirements and operational stakeholders, ensuring operations teams get answers without needing to have detailed technical background

QUALIFICATIONS

• 2+ years of experience in an analytical or operational role with a focus on data and analytics. Functional experience working with quality processes and data is a plus.
• Demonstrated experience working with cross-functional partners to use data to drive results and initiatives.
• Strong technical and analytical skills, including proficiency in SQL and familiarity with data visualization tools (e.g., Sigma, Hex, or similar). Familiarity with modern data warehouses (e.g., Snowflake) and analytics workflows (e.g., dbt, ELT) 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
• Ability to translate complex analyses into clear, actionable recommendations, enabling technical and operational stakeholders to make informed decisions and drive measurable improvements.
• Comfortable operating in evolving environments where processes, systems, and data structures are still being built and refined.
• Proactive mindset with a desire to deeply understand operational processes and continuously improve them through data.

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.

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 $100,000 - $125,000. 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.