As a Data Scientist Tech Lead for Verily, you will lead a team of data scientists that work cross-functionally with Verily’s clinical, software and science teams to build predictive models and algorithm capabilities. These efforts combine bio-sensor data, EHR and claims data with traditional clinical and lab-based tests designed to gather and analyze biological, physiological, behavioral and environmental variables.
You will leverage specialized and robust cloud infrastructure to capture and analyze digital health data. In this position, you will be a strong domain and technical leader, helping shape the product direction, whilst guiding your team to bring analytical rigor and statistical methods to the challenges of modeling large, diverse and complex data sets to measure disease status, progression and clinical outcomes. To do this, 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 device 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 our website.
- Build, lead and nurture a team of talented and diverse data scientists.
- Work with large, complex data sets. Solve difficult, non-routine analysis problems.
- Mentor your team to iterate on and build world-class analytic models using a combination of statistical, signal processing, and machine learning approaches.
- Develop quality control and pre-processing tools for a broad range of digital health data types.
- Collaborate cross-functionally with a wide variety of people and teams and effectively communicate highly technical results and methods clearly.
- Advanced degree in a quantitative discipline (e.g., statistics, computational biology, biomedical engineering, computer science, applied mathematics, or similar), or equivalent practical experience.
- Demonstrated experience with machine learning, exploratory data analysis, statistical modeling and signal processing.
- Demonstrated prior management experience
- Demonstrated domain experience with EHR data and clinical informatics
- Strong communication and collaboration skills
- At least 10 years of data analysis and modeling experience, with 5+ years of hands-on technical leadership and people management experience.
- Demonstrated expertise in problem solving and prioritization in a dynamic environment with multiple stakeholders.
- Experience working closely with healthcare subject matter experts.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1