Data Scientist II (Sleep)

WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level through a deeper understanding of their bodies and daily lives.

As a Data Scientist II on the Sleep Data Science team, you’ll help develop technology at the core of the business – high quality sleep tracking is a fundamental part of the WHOOP experience. In collaboration with MLOps, product managers, and research scientists, you'll develop algorithms to transform wearable sensor data into meaningful insights for users to evaluate their sleep. You’ll work with data from a variety of sources including processed time series data generated by sensors on the WHOOP Strap, data collected from “gold-standard” devices, and data entered manually by WHOOP members via the mobile application. Using these data sources, as well as drawing upon clinical theory and evidence, you will design, train, and deploy machine learning algorithms to analyze sleep data. We’re looking for someone who has experience developing ML models with large datasets in Python and who is excited about the use of wearables in the health and wellness space.

RESPONSIBILITIES:

• Develop statistical and machine learning models to solve complex problems with data of varying structures
• Conduct research on specific health and physiological problems and integrate clinical research into the development of algorithms
• Productionize models and algorithms, monitor model performance and the production service in the field
• Work with MLOps engineers to stand up production backend APIs in Python that pass data through inference pipelines with trained machine learning models
• Reports to the Sleep Data Science Manager

QUALIFICATIONS:

• Bachelor's Degree in Statistics, Data Science, Applied Mathematics, Computer Science or a related field. Master’s preferred.
• 2+ years of full-time professional experience in a related area
• 2+ years experience applying advanced mathematical and statistical techniques
• Strong python programming skills and substantial experience with scientific python packages
• A strong interest in improving people’s health and well-being
• Experience working with processed physiological time series data such as that from PPG, ECG, or EEG sensors is a plus
• Experience deploying services and maintaining live code through logging and monitoring within a production environment is a plus.