Job Title: Director of Biostatistics

Work Location: Middlesex County, MA

Summary:

Seeking an experienced biostatistics leader to drive statistical strategy and execution for early-phase oncology clinical trials. This role is responsible for designing, modeling, and analyzing Phase I/II studies, authoring statistical analysis plans, and ensuring scientific rigor in the development of novel cancer therapies.

Responsibilities:

• Lead the statistical design and execution of early-phase oncology clinical trials, including sample size calculations, randomization, and adaptive design simulations.
• Implement and execute advanced dose-finding methodologies such as Bayesian Optimal Interval (BOIN) and cohort expansion models for trial-level analysis.
• Author and validate statistical analysis plans, design shell tables/listings/figures, and write statistical sections of clinical study reports.
• Develop and maintain dynamic data visualizations and dashboards (using R/Shiny) to monitor dose escalation, safety signals, and biomarker trends in real time.
• Translate complex statistical outputs into clear, impactful visual presentations for leadership, investors, and scientific advisory boards.
• Ensure trial data compliance with CDISC standards (SDTM, ADaM) and oversee technical deliverables from external programming and biostatistics vendors.
• Prepare statistical data packages and rationales for regulatory submissions, including Investigational New Drug (IND) applications and expedited filings.
• Collaborate closely with cross-functional study teams, integrating pharmacokinetic and biomarker data into exploratory analyses to identify early safety or efficacy signals.

Qualifications:

• Ph.D. in Biostatistics or Statistics with 6+ years of relevant experience, or M.S. in Biostatistics or Statistics with 8+ years of experience in biotech/pharma.
• Minimum 3 years of hands-on experience designing, modeling, and analyzing early-phase oncology trials (Phase I/II).
• Demonstrated success in leading oncology trials from protocol design through final clinical study report.
• Advanced programming skills in R and SAS, including experience with trial simulations, oncology datasets, and visualization tools such as Shiny.
• Expertise in Bayesian trial design, especially BOIN, and adaptive trial methodologies.
• Strong knowledge of early oncology endpoints (e.g., DLT, PFS, ORR, RECIST 1.1, Lugano criteria).
• Experience with CDISC data standards (SDTM, ADaM) and regulatory submission requirements.
• Outstanding written and verbal communication skills, with the ability to explain complex statistical concepts to diverse audiences and influence cross-functional teams.
• Ability to thrive in a fast-paced environment with frequent data iterations and evolving priorities.

Published Category: Biostatistics & Data Sciences