Staff Quantitative Scientist
at Verily
Location
Dallas, Texas; Boston, Massachusetts; San Bruno, California; Raleigh, North Carolina
Compensation
$130k–$196k USD
Type
full time
Posted
2 months ago
Market range · function + seniority
p25 · target · p75 · n=783
Posted $196k · in the market band
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Job description
Who We Are
Verily Health is a data platform and technology company purpose-built to power AI-enabled precision health solutions that accelerate research and improve care for individuals and communities. Uniquely positioned at the intersection of technology, data science, and healthcare, Verily transforms multimodal health data into insights, models, and actions that make healthcare more personalized, predictive, and precise.
Description
As a Staff Quantitative Scientist at Verily you will have the unique opportunity to shape the future of healthcare analytics, tackling complex challenges in personalizing patient care and the development of new approaches to health care delivery. You will be at the forefront of applying cutting-edge statistical and computational techniques to real-world health data, driving innovations that can transform patient outcomes and advance public health.
Responsibilities
Design and analyze health studies using statistical and epidemiological methods to support decision-making.
Oversee research projects from design to dissemination, employing scientific rigor by ensuring quality of statistical analysis plans, data, analytical code, and output
Work with Care Delivery, Product, and Commercial teams to demonstrate effectiveness of Verily’s portfolio and develop metrics that enable strategic tracking based on evidence generation
Design and carry out analyses of clinical outcomes, health care costs, and utilization, including KPIs and performance guarantees.
Work with cross functional teams to test service delivery models, and evaluate the impact of new product features and AI on engagement and clinical outcomes.
Qualifications
Minimum Qualifications
Master’s in Health Economics, Biostatistics, Epidemiology, Data Science, or related field
5+ years in statistical analysis or biostatistics within healthcare.
Proficiency in Python or R for statistical programming.
Experience with health economic and epidemiological methods and study designs.
Preferred Qualifications
PhD in Health Economics, Health Services Research, Biostatistics, Epidemiology, Data Science, or related field
Experience with observational healthcare data including claims or electronic health records
Experience with advanced statistical or machine learning methods.
Previous experience working with products and/or digital health solutions.
Strong publication record and experience in study design.
Qualified applicants must not require employer sponsored work authorization now or in the future for employment in the United States.
The US base salary range for this full-time position is $130,000 - $196,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Verily Health Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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