1 month ago
Base Salary
$150k - $215k/yr
Responsibilities
- Develop verification and validation methodologies for sensor algorithms and biosensor systems, including test design, reference-data comparison, metrics, acceptance criteria, and readiness assessment.
- Collaborate with cross-functional engineering, research, firmware, and laboratory teams on representative data collection, algorithm evaluation, failure-mode characterization, and deployment readiness.
- Apply signal processing, statistical analysis, and machine learning to physiological time-series data.
- Build and maintain workflows, dashboards, diagnostic tools, regression-testing systems, monitoring, and data-quality assessment capabilities.
- Contribute to software development, debugging, testing, and validation for analytical tools and algorithms.
- Communicate technical findings through documentation, reports, visualizations, and actionable recommendations.
Requirements
- Bachelor’s or master’s degree in electrical engineering, biomedical engineering, applied mathematics, statistics, computer science, or a related quantitative field, or equivalent practical experience.
- At least 5 years of industry or research experience in signal processing, machine learning, statistical analysis, algorithm validation, or related quantitative methods.
- Experience analyzing time-series data and using filtering, spectral analysis, peak detection, and windowing.
- Experience independently designing and driving validation studies, including test methodology, reference-data comparison, performance evaluation, acceptance criteria, or failure-mode investigation.
- Ability to investigate complex technical challenges, identify root causes, and deliver solutions across algorithm, sensor, data, and system domains.
- Proficiency in Python and/or C and experience developing reliable data-processing, analysis, or algorithm-validation tools.
- Strong statistical inference and experimental-analysis skills, including method selection, result interpretation, and communication of trade-offs.
- Experience with large datasets and engineering or data infrastructure such as Git, CI/CD systems, cloud platforms, or data warehouses.
- Strong written and verbal communication skills.
- Commitment to using AI tools while maintaining high-quality standards.
About WHOOP
WHOOP builds a wearable health and performance tracker paired with an analytics app that measures sleep, recovery, and strain for athletes and health‑conscious consumers. Its business model combines device sales with a recurring membership that unlocks coaching features and insights. Founded in 2012 and headquartered in Boston, the privately held company also serves enterprise wellness programs and sports organizations seeking continuous performance monitoring.