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 Training 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
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