Data Scientist, Signal Processing and Machine Learning
Job location
San Bruno, CA, US
Type
Full Time
Responsibilities:
Develop signal processing and machine learning-based digital measures from physiological signals collected by wearable sensors (such as accelerometers).
Utilize and contribute to Verily’s big data infrastructure to deploy algorithms for production use.
Work cross-functionally to plan and execute clinical studies for analytical and clinical validation of digital measures.
Analyze large, complex real-world datasets involving physiological sensors, and clinical and behavioral data to generate scientific evidence and motivate product direction.
Communicate highly technical results and methods clearly to cross-functional teams, both internally and externally.
Requirements & Skills:
MS degree in a quantitative discipline (statistics, computer science, biomedical engineering, or similar) with 3+ years of industry experience.
Experience developing signal processing and machine learning algorithms.
Experience with Python and SQL.
Experience with statistical data analysis and data visualization.
Experience analyzing and developing algorithms using physiological signals (such as photoplethysmography and accelerometer).
Familiarity with software engineering principles and experience deploying algorithms in production environments.
Experience developing deep learning and generative AI-based algorithms using TensorFlow or PyTorch, and knowledge of the latest architectures.
PhD degree in a quantitative discipline (e.g., statistics, computer science, biomedical engineering, or similar).
