Staff Quantitative Scientist

Verily

Staff Quantitative Scientist applying statistical and computational methods to Verily’s health data platform. Designing studies and evaluating healthcare outcomes, costs, utilization, products, and AI-enabled care solutions.

Posted 8/5/2026full-timeDallas • California, Massachusetts, North Carolina, Texas • 🇺🇸 United StatesLead💰 $130,000 - $196,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in statistical analysis and epidemiological methods to design and evaluate health studies, ensuring quality and effectiveness in healthcare decision-making. Proficient in Python or R for statistical programming and experienced in analyzing observational healthcare data.

Highest-signal resume keywords

Master’s In Health EconomicsStatistical AnalysisBiostatisticsProficiency In PythonExperience With Health Economic Methods

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical AnalysisEpidemiological MethodsData ScienceAdvanced Statistical MethodsMachine Learning MethodsStudy DesignHealth Economic MethodsObservational Healthcare DataClinical Outcomes AnalysisKPI Development

Industry Keywords

HealthcareDigital Health SolutionsClaims DataElectronic Health RecordsCross-Functional CollaborationEvidence GenerationService Delivery ModelsPublication RecordPerformance GuaranteesAI Impact Evaluation

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design and analyze health studies using statistical and epidemiological methods to support decision-making
Oversee research projects from design to dissemination
Ensure quality of statistical analysis plans, data, analytical code, and outputs
Work with Care Delivery, Product, and Commercial teams to demonstrate the effectiveness of Verily’s portfolio
Develop metrics enabling strategic tracking based on evidence generation
Design and conduct analyses of clinical outcomes, health care costs, and utilization, including KPIs and performance guarantees
Collaborate with cross-functional teams to test service delivery models
Evaluate the impact of new product features and AI on engagement and clinical outcomes

Requirements

What you’ll need

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
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

Benefits

Comp & perks

Bonus
Equity
Competitive benefits
Flexibility and resources supporting whole-person well-being
Opportunities to grow
Accommodation support for applicants