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Data Science Tech Lead

2 months ago

Boston, Massachusetts, United States whoop Full time
Unlock Human Performance with WHOOP

As a Staff Data Science Tech Lead on our Training team, you will play a key role in developing algorithmic features and metrics that capture aspects of daily movement, exercise, and training. Leveraging various data sources, you will work with a team of data scientists to design, train, deploy, and maintain machine learning algorithms to provide insights to members on a wide range of topics.

Responsibilities:
  • Design, develop, and implement WHOOP algorithms using large-scale machine learning models to capture unique aspects of an individual's behavior and physiology.
  • Work closely with a team of data scientists to develop algorithms that power member-facing features, managing a portfolio of projects in various stages of development at any given time.
  • Conduct literature reviews and research projects to power evidence-based features for Members, continuously improving the team's knowledge of physiological and data science methods.
  • Collaborate with WHOOP Labs and our in-house clinical research team to design novel studies to collect 'ground truth' data necessary for training machine learning algorithms.
  • Create, improve, and maintain production services that provide analysis for movement, exercise, and training in collaboration with MLOps Engineers.
  • Work with Data Engineers to improve data pipelining, tooling for machine learning, and systems for quality and validation.
  • Mentor other data scientists on the team, regularly providing actionable feedback for more junior data scientists on both technical and non-technical aspects.
  • Periodically serve as the on-call data scientist to respond in real time to incidents affecting production services.
Qualifications:
  • Bachelor's Degree in Mathematics, Statistics, Computer Science, or a related field.
  • 7+ years of full-time professional experience in a related area.
  • 7+ years experience applying advanced mathematical and statistical techniques.
  • Significant experience working with time series data, preferably with wearable data applications.
  • 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.