Data Scientist, Signal Processing
South San Francisco, CA
VerilyVerily is focused on using technology to better understand health, as well as prevent, detect, and manage disease. Our mission is to bring together technology and life sciences to uncover new truths about health and disease.
Verily is an Alphabet company combining a data-driven, people-first approach to bring the promise of precision health to everyone, every day.
Our team combines expertise in healthcare, data science and technology to improve the health and well-being of our communities. We are developing the infrastructure and solutions to harness the profusion of health information for good. Our data-driven solutions span three primary areas: research, care and innovation. Programs include Project Baseline - our research initiative to increase participation and evidence generation in clinical research; Onduo - our personalized virtual care platform, which includes connected tools, lifestyle coaching and clinical support; and Debug - our effort to reduce the threat of mosquito-borne diseases by combining machine learning with sterile insect technique. We’re also actively working to combat the spread of COVID-19 through new programs like Healthy at Work.
As a Data Scientist for Verily, you will work cross-functionally with Verily's hardware, software, clinical and science teams to create signal processing and machine learning algorithms and methods for processing novel cardiovascular system bio-sensor data and clinical data. These efforts combine wearable sensing with traditional clinical tests and health outcomes in an effort to change the way various diseases are understood and treated. You will apply your skills to develop signal processing algorithms and analytic methods to diverse and complex data sets, often derived from noncontrolled real-world settings. You will deliver key analyses for motivating product direction, build reusable analysis tools and work closely with hardware engineers, software engineers, product managers and clinicians to deliver user-facing products. You will bring analytical rigor, as well as machine learning and statistical methods to create models and inferences on both population and individual levels. You will leverage the latest information from the scientific literature and evolving guidance from the clinical community and Verily SME’s.
- Deliver signal processing and machine learning algorithms for novel devices and sensors in the cardiovascular domain.
- Work closely with the hardware and clinical teams to plan experiments, collect real-world data and deliver key analysis for motivating product direction.
- Work with the hardware and firmware teams for on-device implementation of algorithms.
- Develop quality control and pre-processing tools for a variety of bio-sensor and clinical data streams.
- Communicate highly technical results and methods clearly, as well as, interact cross-functionally with a wide variety of internal and external people and teams.
- MS or PhD degree in a quantitative discipline (e.g., statistics, computer science biomedical engineering, or similar) or equivalent practical experience.
- Experience with Python.
- Experience developing signal processing algorithms.
- Experience with exploratory and statistical data analysis (such as linear models, multivariate analysis, predictive modeling and stochastic models).
- Hands-on experience with developing algorithms for hardware implementation, data collection and analysis.
- Familiarity with software engineering practices and experience developing production software.
- Experience with the analysis of cardiovascular sensors and clinical data.
- Demonstrated willingness to both teach others and learn new techniques.
- 1 year of relevant work experience (i.e., as a statistician, data scientist, etc.), including deep expertise and experience with statistical data analysis.
* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net
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