Overview

About the Project AACR Project Genomics, Evidence, Neoplasia, Information, Exchange (GENIE) is a publicly accessible international cancer registry of real-world clinico-genomic data assembled through data sharing between 20 of the leading cancer centers in the world. Through the efforts of strategic partners Sage Bionetworks and cBioPortal, the registry aggregates, harmonizes, and links clinical-grade, next-generation cancer genomic sequencing data with clinical outcomes obtained during routine medical practice from cancer patients treated at these institutions. Job Summary: AACR Project GENIE is seeking an experienced Senior Biostatistician to provide statistical leadership across an international real-world clinico-genomic data consortium. This individual will serve as the primary statistical resource for the project, partnering with clinicians, scientists, data managers, and external collaborators to design, execute, and interpret observational research studies using real-world oncology data. The successful candidate will independently develop statistical analysis plans, contribute to study protocols and publications, design appropriate analytical methodologies, and perform statistical programming in R. This role requires expertise in real-world data, including electronic health records, cancer registries, genomic sequencing data, and longitudinal clinical outcomes, as well as the ability to translate scientific questions into rigorous and reproducible statistical analyses. This role is ideal for a senior biostatistician who enjoys working independently and leading the statistical design, programming, and interpretation of multiple concurrent studies within a collaborative multidisciplinary environment. The successful candidate will be a self-starter who takes initiative and balances big picture strategy with execution against project goals, bringing an entrepreneurial, visionary approach and the ability to conceive of, execute, and communicate innovative solutions. Additionally, the successful candidate should bring a strong passion for mission-driven causes and a commitment to advancing cancer research through high-quality, collaborative, statistical science.

Responsibilities

• Serve as the statistical subject matter expert for AACR Project GENIE, providing consultation to investigators, collaborators, and project leadership on study design and analytical strategy.
• Collaborate with investigators, pharmaceutical clients, and academic institutions to design observational studies using real-world clinico-genomic data
• Develop statistical analysis plans (SAPs), define study populations, cohorts, endpoints, and analytical methods.
• Contribute statistical expertise to research protocols, study design, and publication planning.
• Perform statistical programming and analyses using R.
• Interpret results and contribute to manuscripts, abstracts, presentations and consortium reports.
• Willing to experiment with new analytic methods as needed.
• Advise project leadership on appropriate statistical methodologies, and study design.
• Ensure analyses are reproducible, well documented, and adhere to best practices.
• Collaborate with data managers, investigators, and pharmaceutical clients to assess data quality, completeness and fitness for analysis.
• Independently lead the statistical aspects of multiple concurrent observational research studies from study conception through analysis and publication.
• Other duties as assigned.

Qualifications

Education:

• M.S. or Ph.D. in Biostatistics, Epidemiology, Statistics, or a closely related quantitative discipline.

Experience:

• 5+ years of post-graduate experience providing end-to-end statistical support for observational research studies using real-world data (RWD), including electronic health records (EHRs), cancer registries, genomic data, claims data, or other longitudinal clinical data sources.
• Demonstrated experience designing statistical analysis plans (SAPs), contributing statistical sections of research protocols, defining study cohorts, endpoints, and analytical methodologies for observational clinical research.
• Prior peer-reviewed publications as a statistical collaborator.
• Strong proficiency in R is required, including statistical programming, data manipulation, reproducible workflows, and production-quality analytical code.
• Experience applying statistical methods commonly used in oncology and observational research, including survival analysis, Kaplan-Meier estimation, competing risks, longitudinal analyses, regression modeling, propensity score methods, missing data approaches, and sensitivity analyses.
• Experience collaborating with clinicians, scientific investigators, and data management teams to translate research questions into statistically rigorous study designs, with well-honed relationship building skills and outstanding, articulate, and persuasive communication, public speaking, and presentation abilities.
• Experience interpreting and communicating statistical findings to both technical and non-technical audiences, with exceptional strategic thinking and problem-solving abilities and a proven track record of success in solving complex and dynamic situations.
• Entrepreneurial, visionary approach with the ability to conceive of, execute, and communicate innovative solutions.
• Must be a self-starter who takes initiative and can balance big picture strategy and execution against goals.

Preferred Qualifications:

• Python proficiency
• Experience working with clinico-genomic oncology datasets
• Familiarity with REDCap or other EDC platforms
• Experience with Git/GitHub strongly preferred

Employment Type: FULL_TIME