Data Scientist II (Core Physiology)
Boston, MA
WHOOP
Monitor your sleep, strain, recovery, and health with the most advanced fitness and health wearable available today. WHOOP helps you discover data-driven insights for a healthier, more empowered life.RESPONSIBILITIES:
- Develop advanced machine learning models and algorithms for product features. These algorithms will often run on time-series sensor data
- Research, prototype, and deploy algorithms and predictive models, such as classification, forecasting, anomaly detection, change-point detection and signal processing using both conventional and deep learning techniques
- Deploy the models and algorithms in production after testing and documenting the APIs
- Communicate results to technical and non-technical stakeholders
- Identify and build new datasets to enhance the models and decision making
- Reports to the Data Science - Core Physiology, Principal Technical Lead
QUALIFICATIONS:
- Bachelor's Degree or higher in Mathematics, Statistics, Computer Science, Electrical Engineering, Physics, or a related field
- 2+ years of full-time professional experience in applying advanced mathematical and data-driven algorithms in a production environment
- Significant experience working with time series data is preferred.
- Proficient in scientific Python (NumPy, SciPy, scikit-learn, Pandas, XGBoost), SQL, and version control (GitHub)
- Ability to formulate hypotheses, draw conclusions and deliver results
- Excellent verbal and written communication and interpersonal skills
- Ability to present findings to stakeholders and communicate results to all colleagues
- Understanding of exercise physiology or athletic experience is a huge plus
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Classification Computer Science Deep Learning Engineering GitHub Machine Learning Mathematics ML models NumPy Pandas Physics Python Research Scikit-learn SciPy SQL Statistics Testing XGBoost
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