Clinical Biostatistician

Position Objective

The Clinical Biostatistician will provide services to the National Institute on Drug Abuse (NIDA) within the National Institutes of Health. The purpose of this position is to offer biostatistical support to the NIDA IRP investigators.

• Provide biostatistical expertise for research study
• Communicate research findings, disseminate public information, and respond to relevant inquiries
• Provide analytic results using standard statistical procedures, including descriptive statistics, rate standardization, stratification of data, and model building (logistic regression, conditional logistic regression, Cox regression) using SAS, Stata, Epicure, and similar statistical software programs
• Collaborate and work with a team of researchers to develop, iterate, and execute innovative strategies for genomic data integration and modeling/prediction
• Utilize statistical software packages to manage, maintain, and analyze large, complex datasets
• Work with branch staff and research training fellows to provide statistical support for studies based on existing datasets, and assemble datasets for these purposes
• Enter and verify data fields and data dictionaries
• Perform descriptive and missing data analysis
• Apply a variety of data reduction techniques
• Prepare summaries and reports for staff review
• Write statistical sections in manuscripts and interpret referee comments
• Provide description of statistical methods in manuscripts and respond to referee comments
• Analyze, interpret, communicate, and document epidemiologic data and results
• Participate in and contribute to different aspects of the research study through study planning, decision-making, problem-solving, and strategic analysis
• Present data, prepare charts, tables, and graphs using PowerPoint, Excel, Stata, Sigmaplot, or Origin for scientific monographs, book chapters, and professional presentations
• Write code to execute data analysis, visualize, interpret, and contextualize results
• Perform data cleaning (identifying and correcting data entry errors and/or missing values) and data transformation (creating and categorizing variables and imputing data)
• Stay abreast of relevant science, research, regulatory, and policy-related issues
• Conduct literature reviews and collaborate on research publications
• Research and review literature to retrieve targeted clinical or scientific information
• Consult with staff on application of statistical methods to address key study scientific aims
• Provide literature review related to analyses used in comparable studies
• Develop training strategies and implement training activities for internal and external researchers
• Integrate data from multiple sources into SAS datasets
• Develop and implement new research and study designs using appropriate statistical methods
• Provide consultation on use of statistical methods and software packages to other staff
• Research and analyze new developments in biostatistical methods and applications
• Provide statistical justification per research protocol
• Run validation
• Meet with lab members to present updates
• Provide statistical analysis per manuscript