RESPONSIBILITIES:
- Build statistical models using techniques such as causal modeling and mediation analysis to provide members with insights about how their behavior affects their WHOOP metrics
- Work with Data Engineers to improve data pipelining, tooling for machine learning, and systems for quality and validation
- Work with MLOps Engineers to build robust, scalable, and efficient machine learning pipelines for deployment and continuous improvement
- Conduct research on the use of wearable sensors to analyze primary and secondary end-points derived from metrics and the implications of this analysis on overall health of the user
- Design data collection studies to improve inference of health insights and demonstrate the efficacy of WHOOP coaching in improving member health
- Periodically serve as the on-call data scientist to respond in real time to incidents affecting production services
QUALIFICATIONS:
- Bachelor's Degree in Statistics, Data Science, Applied Mathematics, Computer Science or a related field (Master’s preferred)
- 5+ years of full-time professional experience in a related area
- 5+ years experience applying advanced machine learning and statistical techniques
- Significant experience working with time series data, causal modeling, probabilistic methods
- Proficiency in scientific Python and SQL
- Experience deploying services and maintaining live code through logging and monitoring within a production environment
- Excellent verbal and written communication skills
- Preferred Qualifications: Experience in software engineering, including the development, deployment, and maintenance of production-quality software.
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