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GAP SOLUTIONS INC

Clinical Biostatistician (51735)

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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.

Duties and Responsibilities:

  • Provide biostatistical expertise for the 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. 1
  • Collaborate and work with a team of researchers to develop, iterate and execute innovative strategies for genomic data integration and modeling/prediction.
  • Utilizes statistical software packages to manage, maintain and analyze large, complex statistical datasets.
  • Work with branch staff and research training fellows to provide statistical support for studies based on existing data sets; work with staff to assemble data sets for these purposes. 2
  • Enter and verify data fields and data dictionaries.
  • Perform descriptive and missing data analysis.
  • Applies a variety of data reduction techniques.
  • Prepare summaries and reports for staff review.
  • Write statistical sections in manuscripts; work with research staff to interpret referees’ comments on manuscripts. 3
  • Provide description of statistical methods in manuscripts; work with research staff to respond to and interpret referees’ comments.
  • Provide biostatistical expertise for the research study.
  • Analyze, interpret, communicate and document epidemiologic data and results.
  • 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.
  • 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 software such as PowerPoint, Excel, Stata, Sigmaplot, or Origin that can be used for scientific monographs, book chapters, and professional presentations (including poster and oral presentations).
  • Write code to execute data analysis, visualize and provide interpretation and context to results of analysis.
  • Enter and verify data fields and data dictionaries.
  • Perform descriptive and missing data analysis.
  • Applies a variety of data reduction techniques.
  • 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 and current research, as well as relevant regulatory and policy-related issues.
  • Conduct relevant literature reviews and collaborate on relevant research publications.
  • Research and review literature to retrieve targeted clinical or scientific information from publicly available resources.
  • Consult with staff on the application of statistical methods to address the key study scientific aims of the study.
  • 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 data sets.
  • 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