Senior Sensor Intelligence Engineer (Tools & Validation)

Reposted 4 Hours Ago
Be an Early Applicant
Boston, MA, USA
Hybrid
150K-215K Annually
Senior level
Fitness • Hardware • Healthtech • Sports • Wearables
Power your performance with 24/7 data
The Role
Designs and executes statistical validation studies for physiological sensing algorithms, evaluating accuracy, reliability, robustness, uncertainty, generalizability, and equity. Analyzes experimental and production data, develops equivalence and non-inferiority analyses, creates reproducible validation workflows, and assesses performance across demographic and physiological groups. Partners with scientists, engineers, product managers, and clinical teams to establish validation practices and translate complex findings into product improvements.
Summary Generated by Built In

At WHOOP, we’re on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.

WHOOP is seeking a Senior Sensor Intelligence Engineer to help develop, validate, and scale the sensor algorithms and tools that transform noisy physiological signals into meaningful member insights. As part of a cross-functional team spanning Sensor Intelligence, Hardware, ML Research, WHOOP Labs, Firmware, Apparel & Accessories, and other engineering disciplines, you will develop robust algorithm verification and validation methodologies, evaluate sensor and algorithm performance against appropriate reference data, build diagnostic and analysis tools, characterize failure modes, and help determine algorithm readiness for real-world deployment across our diverse member population.

RESPONSIBILITIES:
  • Develop end-to-end verification and validation methodologies for sensor algorithms and biosensor systems, including test design, reference-data comparison, performance metrics, acceptance criteria, and readiness assessment across large-scale datasets

  • Partner with Data Science, WHOOP Labs, Research, Firmware, and other engineering teams to design representative data collections, evaluate algorithm performance against reference measurements, characterize failure modes, and determine readiness for real-world deployment

  • Apply signal processing, statistical analysis, and machine learning techniques to physiological time-series data to identify performance opportunities, investigate algorithm failures, and improve sensor-derived insights

  • Build and maintain scalable workflows, dashboards, and diagnostic tools for algorithm validation, regression testing, performance monitoring, data quality assessment, and sensor behavior across diverse populations and use cases

  • Contribute to software development, debugging, testing, and validation processes, ensuring analytical tools, algorithms, and results meet production-quality standards

  • Communicate findings through clear technical documentation, reports, and visualizations that enable cross-functional teams to make informed product and engineering decisions

QUALIFICATIONS:
  • 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

  • 5+ years of industry or research experience working with signal processing, machine learning, statistical analysis, algorithm validation, or related quantitative methods

  • Experience analyzing time-series data and applying core signal processing techniques such as filtering, spectral analysis, peak detection, and windowing

  • Demonstrated experience independently designing and driving validations studies, including one or more of test methodology development, reference-data comparison, performance evaluation, acceptance-criteria definition, or failure-mode investigation.

  • Proven track record of investigating intricate or ill-defined technical challenges, pinpointing root causes, and delivering solutions across algorithm, sensor, data, and system domains

  • Proficiency in Python and/or C, with experience developing reliable tools or software for data processing, analysis, or algorithm validation

  • Strong foundation in statistical inference and experimental analysis, including the ability to select appropriate methods, interpret results, and communicate analytical trade-offs

  • Experience working with large datasets and modern engineering or data infrastructure such as Git, CI/CD systems, cloud platforms, or data warehouses

  • Strong written and verbal communication skills, with the ability to translate complex technical findings into concise documentation, visualizations, and actionable recommendations

  • 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.

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. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Skills Required

  • Advanced degree in Statistics, Biostatistics, Data Science, Applied Mathematics, Biomedical Engineering, Epidemiology, or a related quantitative discipline, or equivalent practical experience
  • At least 3 years of experience applying statistical methods to complex experimental or observational datasets
  • Strong foundation in statistical inference, hypothesis testing, regression, experimental design, uncertainty quantification, and validation study design
  • Proficiency analyzing large datasets using Python, R, or similar statistical programming tools, plus SQL and large-scale data environments
  • Experience with physiological, wearable, biomedical sensor, time-series, or longitudinal data
  • Familiarity with advanced statistical methodologies such as mixed-effects models, Bayesian statistics, survival analysis, fairness analysis, or parity analysis
  • Strong communication and collaboration skills, including translating complex statistical findings for technical and non-technical stakeholders
  • Commitment to using AI tools while maintaining high-quality standards
  • Experience with equivalence, non-inferiority, causal inference, method-comparison, machine learning, or signal-processing algorithm evaluation

What the Team is Saying

Josh
Manan Dedhia
Anahis

WHOOP Compensation & Benefits Highlights

  • Parental & Family Support — Paid parental leave is described as generous, with added flexibility through phased return-to-work options, which feedback suggests supports families during transitions.
  • Wellbeing & Lifestyle Benefits — A wellness stipend, complimentary WHOOP memberships, and unique programs like a sleep-performance bonus reflect a strong emphasis on healthy habits and everyday wellbeing.
  • Healthcare Strength — Medical, dental, and vision coverage are described as comprehensive, often complemented by mental health support and company-paid protections such as life and disability insurance.

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The Company
HQ: Boston, MA
500 Employees
Year Founded: 2012

What We Do

At WHOOP, we’re on a mission to unlock human performance. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable device and performance optimization platform has been adopted by many of the world's greatest athletes and consumers alike.

Why Work With Us

At WHOOP, we’re focused on building an inclusive and equitable team with a strong sense of belonging for everyone—increasing representation in every way as our team grows. We believe that our differences are our source of strength—so much so it’s one of our core values.


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WHOOP Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 4 days a week
HQBoston, MA
Limerick, Limerick, V94 4D83 Ireland
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