Senior Biostatistician

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.

The Senior Biostatistician provides statistical and study design leadership across the product lifecycle, from feasibility and preclinical evaluation through clinical validation and post-market monitoring. This role partners cross-functionally with medical, product, engineering, data science, regulatory, and operations teams to define study objectives, estimands, analysis strategies, and decision criteria using diverse data sources. The Senior Biostatistician identifies risks to scientific integrity, bias, generalizability, regulatory interpretation, and product decision-making, and recommends practical approaches that balance rigor, feasibility, and timelines.

• Leads statistical design and analysis across the entire product lifecycle, from early stage feasibility through validation and post-market activities.
• Partners with cross-functional teams to translate scientific and product questions into clear objectives, estimands, analysis plans, and decision criteria.
• Analyzes clinical, experimental, observational, real‑world, and operational datasets to generate interpretable evidence.
• Evaluates data quality, bias, missingness, generalizability, model performance, and other factors that affect study interpretation.
• Communicates study designs, assumptions, results, limitations, and recommendations to cross-functional audiences, including clinical, product, engineering, regulatory, and leadership stakeholders, through protocols, reports, presentations, dashboards, and cross-functional discussions.

• Master’s degree or higher in biostatistics, statistics, epidemiology, data science, bioinformatics, biomedical informatics, or a related quantitative field.
• 5+ years of experience applying statistical methods to clinical, biomedical, health technology, medical device, pharmaceutical, diagnostics, or life sciences research.
• Demonstrated expertise in designing and analyzing observational studies, interventional clinical studies, and real-world data studies that support evidence generation or product decision-making.
• Experience programming in R and/or Python for analysis of complex life science, biomedical or healthcare datasets.

• Experience with a range of evidence generation including diagnostics, devices, digital health, or AI/ML-enabled clinical products, and diverse healthcare data sources, including EHR, claims, registry, device-generated, sensor, imaging, laboratory, or patient-reported data.
• Experience working with products in a health-regulated environment (e.g. submissions involving the FDA or other health authorities).
• Hands‑on experience generating evidence from digital product data as a primary data source, including handling missingness, measurement error, and analytic approaches specific to continuous digital measures.
• Experience with Bayesian methods, adaptive trial designs, or causal inference methods for observational/RWD studies.
• Experience using reproducible research workflows, version control systems such as Git, and modern coding tools, including AI-assisted development tools where appropriate.

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…