Data Analyst Dietary Behavior Research

Location : IC: CC Street: 10 Centre Dr Bldg.: 10 Room: 2B07 City: Bethesda State & Zip: MD 20892

Weekly Hours FT: 3040 hours per week Total No. of Hours : 40

Overall Position Summary and Objectives

This position reports to the Section Chief for The Dietary Behaviours and

Biopsychosocial Section of the Translational Biobehavioural and Health Disparities Branch of the NIH Clinical Centre. Primary responsibilities include data entry management and analysis for clinical studies looking at the intersection of nutrition diet and biopsychosocial health.

Min Education Bachelors

Payrate $38.74 hourly on W2

Certifications & Licenses

• None required

Skills (Ranked by Priority)

1. Scientific Data analysis
2. Statistical modelling
3. Database management
4. Data presentation

Software

• R
• SPSS

Field of Study

• Information Sciences

Statement of Work Details

Collects and analyses data for a variety of studies.

• Provide final data sets for each project.
• Perform statistical analysis for each project.
• Construct systematic processes for data entry and quality assurance from project onset through analysis.
• Perform data entry in support of a number of different systems and programs both numerical and text format.
• Organize implement maintain and archive data.
• Work with staff to gather and analyse information from users primarily principal investigators (PIs) needed for the development or modification of CRFs and accompanying interface relating to data collection storage and access.
• Coordinate and perform data entry. 1
• Perform quality checks to ensure consistency integrity and robustness of data.
• Provide analysis analytical modelling and/or data visualization on data sets using relevant data tools.
• Assist in determining variables and data collection for study protocol development (ex. literature reviews)
• Provides assistance in data collection at multiple locations including Clinical Centre community study intervention site or remote.
• Participates in internal (NIH) or external (nonNIH) trainings as required for new or changing study requirements

Organizes data to provide functional reporting.

• Create data workflow processes.
• Ensure that appropriate variables are captured in the constructed databases.
• Format databases to allow merging of spreadsheets for statistical analyses and to optimize planned analyses.
• Record data into a format appropriate for processing.
• Apply statistical techniques to produce meaningful tables and graphs using appropriate software.
• Provide support with data sharing including public repositories.
• Work with staff to prepare and standardize data for the database.
• Perform routine and general data management.
• Prepare tables and figures from data analyses.
• Perform database searches and assemble data sets.

Creates and maintains a variety of reports.

• Create systematic documentation on reporting (completeness changes or errors).
• Provide draft results and output for statistician review.
• Maintain data for past and present studies.
• Compile results of analysis projects into detailed reports.
• Maintain databases for tracking and monitoring activities.
• Work with staff to curate data retrieve records and generate reports
• Complete data analyses and assist with draft manuscript for study results

Manages storage and backup systems.

• Maintain and update electronic copies of all databases and data dictionaries developed for projects.
• Maintain and update accurate and complete filing of data following data entry / QA.
• Perform data auditing for quality assurance of data entry review.
• Follow established policies and procedures for the quality assurance of all study collection interfaces storage and access.
• Maintain a variety of computerized files and records.
• Maintain and improve the existing data pipeline for processing and storing data.

Participates in the development and design of databases for tracking and statistical purposes that incorporate multiple data fields required by scientists.

• Develop and maintain data management and quality assurance/quality control procedures that improve the transparency consistency accuracy and comparability of data which supports the integrity of research.
• 3.Document methods and results sufficiently to ensure reproducibility by other researchers.
• Develop maintain and update program database and spreadsheet.
• Participate in the design and implementation of data reporting tools.
• Provide support for requests pertaining to new studies for electronic data capture or storage from investigators review of current system or the creation and editing of CRFs and electronic capture tools/interface.
• Maintain databases and spreadsheets related to various data sharing activities.
• Provide support for all data sharing related activities; create and maintain data access and data submission tracking systems and reports to be presented to senior program leadership.
• Maintain databases and spreadsheets for tracking and analysing submission of datasets.

Assists with coordination of statistical data analysis for numerous ongoing studies by collecting organizing and tracking information.

• Develop data dictionaries for each database.
• Enhance data management and document data sharing practices.
• Formulate appropriate data auditing plan and strategy to provide services to studies that are active and ongoing as required to ensure that the quality of the data meets the study goals and quality standards.
• Prepare databases and reports for staff; perform various tracking and analysis of branch data to include spreadsheet preparation and interpretation.
• Design develop and maintain databases Listservs spreadsheets PowerPoint presentations and other computer applications.
• Meet with data customers inside and outside the research branch to assess database requirements (ex BTRIS for RedCap)

Manages projects and quickly responds to inquiries about status.

• Perform database analysis to look for incomplete data elements.
• Identify possible trends and patterns in the data; communicate relevant findings that support problem solving and decision making.
• Track and solve problems during the data entry and QA processes.
• Provide description of procedures used to perform data quality assurance; update as procedures are developed.
• Provide log and description of projectrelated data associated data management problems that were solved and their resolution.
• Allocate quality assurance resources to ensure data validity and fidelity.
• Work with database users to identify and resolve cases of missing data.