As a Research Data Scientist working as part of the COVID-19 Healthy at Work program, you will work cross-functionally with Verily’s clinical, software, product, and science teams to create models of population-level and individual-level health as these relate to maintaining a workplace that is safe during the COVID-19 pandemic. In this position, you will bring analytical rigor and statistical methods to the challenges of minimizing COVID-19 prevalence and spread in a workplace, while accounting for real-time data coming from symptom tracking, infection testing, and other related data streams. You will apply your skills to create and refine epidemiological and other statistical models of disease that leverage the latest information from the scientific literature and evolving guidance from the clinical community. To enable real-world impact, you will deliver key analyses for motivating product direction, build reusable analysis tools, and work closely with software engineers, product managers, and clinicians to deliver user-facing products.
Their team combines expertise in biology, chemistry, physics, medicine, engineering, computer science, and more to create interventions that exponentially improve patient care. They partner with leading life sciences, medical devices, and government organizations to enable fast development, meaningful advances, and deployment at scale. Their work spans many projects, including Project Baseline, the quest to map human health beginning with a 10,000 person observational study; Liftware, stabilizing utensil handles to aid individuals with hand tremor or limited mobility; and Debug, an effort to reduce the threat of mosquito-borne diseases using the sterile insect technique. For more information, please visit their website.
Responsibilities
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- Work with large and complex data sets to solve difficult, non-routine analysis problems, using a combination of statistical and machine learning approaches.
- Develop quality control and pre-processing tools for a variety of data streams.
- Iterate on and build predictive models of individual-level and population-level health and disease from COVID-19 testing, symptom screening, and related data sources.
- Communicate highly technical results and methods clearly, as well as, interact cross-functionally with a wide variety of internal and external people and teams.
Qualifications
Minimum Qualifications:
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- Ph.D. degree in a quantitative discipline (e.g., statistics, computer science, applied mathematics, computational biology, or similar) or equivalent practical experience.
- Experience with Python, R, or similar.
- Experience extracting and cleaning data sets.
- Experience with exploratory and statistical data analysis (such as linear models, multivariate analysis, predictive modeling, and stochastic models).
Preferred Qualifications
- Experience with the analysis of observational clinical/medical/health data.
- Familiarity with software engineering practices and experience developing production software.
- Demonstrated willingness to teach others and learn new techniques.
- 1 year of relevant work experience (i.e., as a statistician, computational biologist, data scientist), including deep expertise and experience with statistical data analysis.
