LMR Technical Group (LMR) is seeking a Biostatistician Data Manager.

Location: Baltimore, MD. Teleworking eligible.

Job Description: The Biostatistician Data Manager will independently provide expert biostatistical support to the Brain Health Equity (BHE) Unit within the Health Disparities Research Section (HDRS) at the National Institute on Aging (NIA). The primary objective is to assist in the statistical design, analysis, and interpretation of data from community-based cohort studies and other research projects led by the Principal Investigator.

Duties and Responsibilities:

• Assists in performing a variety of data management and analytical tasks and organizing complex, large-scale datasets.
  • Provide biostatistical expertise for the research study.
  • Analyze, interpret, communicate and document epidemiologic data and results.
  • 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.
• 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.
  • Enter and verify data fields and data dictionaries.
  • Perform descriptive and missing data analysis.
• Documents analyses performed and prepares progress reports summarizing results.
  • Prepare summaries and reports for staff review.
  • Write statistical sections in manuscripts; work with research staff to interpret referees comments on manuscripts.
  • Provide description of statistical methods in manuscripts; work with research staff to respond to and interpret referees comments.
• Performs a variety of data management and analytical tasks and organizing complex, large-scale datasets.
  • 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.
• Conducts statistical analyses on completed and ongoing studies utilizing a wide range of standard and non-standard statistical software packages for all projects.
  • Write code to execute data analysis, visualize and provide interpretation and context to results of analysis.
  • Perform descriptive and missing data analysis.
  • Perform data cleaning (identifying and correcting data entry errors and/or missing values) and data transformation (creating and categorizing variables and imputing data).
• Reviews and summarizes relevant literature and other sources to develop analytical plans.
  • 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.
• Learns and applies new statistical methods and software packages and p ovides consultation and training to other analysts and staff.
  • Integrate data from multiple sources into SAS data sets.
  • Develop and implement new research and study designs using appropriate statistical methods.
  • Research and analyze new developments in biostatistical methods and applications.
• Deliverables
  • Study Design and Protocol Documentation: Work products related to the design of research studies, development of statistical analysis plans, and study protocols. - Ad-Hoc
  • Data Analysis Reports: Statistical reports, tables, and figures derived from analyses of study data. These should include documentation of the statistical methods used and the results obtained. - Ad-Hoc
  • Data Management Documentation: A comprehensive codebook, data dictionaries, and documentation of data management practices, including data cleaning and coding processes. - Ad-Hoc
  • Compliance and Quality Assurance Reports: Documentation ensuring compliance with Institutional Review Board (IRB) requirements and quality control processes for data integrity and security. - Ad-Hoc
  • Data Sharing Oversight: Ensure that data is shared only with investigators who have approved project proposals and are employed by institutions with active data-sharing agreements. Provide documentation verifying that data distribution adheres to these protocols. - Ad-Hoc
  • Project Proposal Review: Provide assessments to the Principal Investigator regarding the originality of proposed research, recommending alterations in project proposals to avoid duplication of work or efforts within ongoing studies. - Ad-Hoc
  • Presentation and Publication Materials: Prepare manuscripts, abstracts, and presentations, summarizing statistical findings for publication or presentation at scientific conferences. - Ad-Hoc
  • Training Materials: Develop materials for training junior staff or collaborators on statistical methods, data analysis software, and proper data management protocols. - Ad-Hoc
  • Data Sharing Integrity Reports: Document all data-sharing activities, ensuring the security and integrity of distributed data. Use independent judgment to advise on data sharing decisions and maintain records of data requests and transfers. - Ad-Hoc
• Other related duties as assigned

Basic Qualifications:

• Masters or PhD in Biostatistics, Statistics, Bioinformatics, or a related field with specialized experience in statistical analysis of epidemiological data. A bachelor's degree with extensive specialized experience may be considered.
• Proficiency in statistical software such as R, Mplus, SPSS, and other statistical computing software.
• Strong analytical and problem-solving skills, with the ability to independently design and implement statistical analyses for complex datasets.
• Extensive experience in the application of statistical methods to public health, epidemiology, or clinical research, particularly within the context of community-based cohort studies.
• Excellent communication skills, with the ability to clearly explain statistical concepts and results to non-statistical audiences.
• Experience in data management, including data cleaning, coding, and ensuring data integrity.
• Knowledge of regulatory requirements and guidelines related to data protection and research ethics.
• Knowledge of regulatory requirements and guidelines related to data protection and research ethics.
• Ability to work independently and as part of a multidisciplinary team.
• Must have the correctible near vision and the ability to distinguish basic colors.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

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Preferred Qualifications:

Prior experience wo