Senior Biostatistician

Verily•Boston, MA

1d•$130,000 - $196,000

About The Position

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.

Requirements

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.

Nice To Haves

Experience with a range of evidence generation including diagnostics, devices, digital health, or AI/ML-enabled clinical products
Experience working with products in a health-regulated environment (e.g. submissions involving the FDA or other health authorities).
Experience working with diverse healthcare data sources, including EHR, claims, registry, device-generated, sensor, imaging, laboratory, or patient-reported data.
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 developing study protocols, statistical analysis plans, technical reports, and publication-ready analyses.
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.

Responsibilities

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.