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Role Description

The Center for International Blood and Marrow Transplant Research (CIBMTR) provides a unique resource of data and statistical expertise to the scientific community for addressing important issues in hematopoietic cell transplantation and cellular therapies. The Biostatistician II participates in the statistical support of retrospective observational research studies and projects within the CIBMTR and Clinical Services department in alignment with NMDP’s mission, vision, enterprise actions and strategic plan.

• Serve as the lead statistician for retrospective observational research studies, ensuring timely and accurate completion of analyses and submission of manuscripts for publication.
• Collaborate on study design, assess feasibility through preliminary analyses, define study populations, and conduct descriptive, univariate, and multivariate statistical analyses.
• Prepare, clean, and manage datasets for research using statistical software such as SAS and R.
• Ensure reproducibility of programming and analyses through well-documented code, version control, and adherence to internal quality standards.
• Communicate complex statistical concepts clearly to non-statistical audiences, including clinicians, data managers, and external collaborators.
• Contribute to peer-reviewed publications, providing expertise and scientific content regarding study design, study population, statistical methodology and interpretation of results.
• Perform descriptive analyses in response to external data requests through the CIBMTR Information Request Process.
• Partner with database programmers to define new variables, resolve data issues, and guide database structures to support robust statistical analysis.
• Identify and report data anomalies and inconsistencies to ensure data integrity.
• Build and maintain collaborative relationships across disciplines, serving as a statistical and data subject-matter expert for research teams, internal committees, and external collaborators.
• Fulfill requests for datasets and analyses that support the mission of NMDP and its departments.
• Identify opportunities for process improvement, propose and implement efficiency enhancements, and contribute innovative ideas to support team growth and development.

Qualifications

• Knowledge of logistic regression, linear regression, survival analysis and other core statistical methods.
• Research study design principles and statistical standards for observational studies.
• Scientific and therapeutic research concepts, particularly in oncology.
• Advanced analytical techniques and statistical programming, with high-level proficiency in SAS (and optionally R).
• Data cleaning, preparation, and management for retrospective studies.

Requirements

• Independently perform SAS programming and statistical analyses for research projects.
• Interpret and communicate statistical results and study limitations to non-statistical audiences, including clinicians and senior leadership.
• Contribute innovative ideas and process improvements to enhance team efficiency.
• Apply strong problem-solving skills with a proactive and collaborative mindset.
• Document processes meticulously and organize materials for transparency and reproducibility.
• Manage multiple projects simultaneously while meeting deadlines and maintaining organization.
• Communicate effectively through written reports, oral presentations, and public speaking.

Education/Experience

• Master’s degree in Biostatistics or closely related biomedical field where biostatistical design and analyses comprised the primary course of study and application.
• Two+ years of experience in statistical analysis of data from epidemiological or clinical research studies. Experience programming with statistical analysis programs (SAS), logistic regression and survival analysis, and research writing for publication required.
• Proficiency in SAS and/or R.

Preferred Qualifications

• Knowledge of oncology therapeutic areas, treatment pathways, clinical endpoints, and disease progression patterns relevant to cell therapy research studies.
• Familiarity with version control tools (e.g., Git) or reproducible research practices.

Benefits

• Medical, dental, vision, life and disability, accident/critical illness/hospital benefits.
• Well-being, legal, identity theft and pet benefits.
• Retirement plans.
• Paid time off/holidays.
• Leave and incentive plans for eligible employees.