-
Build automated pipelines for analyses and reporting, sharing out code through GitHub or notebooks like Juypter and Observable and connecting code to data in a secured, governed way.
1
-
Perform data analysis, including model building analysis, assessing trends, determining correlations, testing for heterogeneity, and compiling and communicating results to investigators to participate in the interpretation of results and planning of further analyses.
2
-
Perform statistical analysis using novel methods and algorithms.
3
-
Ensure that all data products (dynamic reports, tables, and graphics) are reproducible from the original source data by maintaining clear, commented, and consistent code and organization of files and folders.
4
-
Support pre-and post-doctoral fellows with various web programs and graphing programs and provide technical assistance to team members.
5
-
Performs experimental investigations and similar research projects utilizing extensive applications of mathematical and statistical methodologies.
-
Assist researchers with the planning, implementing, and analysis of research projects.
-
Provide statistical advice and consultation to the investigators in study design, data management, choice and application of statistical methods, data analysis, and interpretation of statistical results.
-
Carry out statistical analyses on issues via descriptive analyses, causal inference, predictive modeling, and other univariate and bivariate and multivariate analytic methods.
-
Develops original computer code and programs for the application of new mathematical and statistical theories for the solution of proposed problems related to various scientific studies.
-
Perform data programming, analysis and presentation by preparing charts, tables and graphs using software such as R, SAS and STATA.
-
Create interim dynamic reports that weave together text, code, output, tables and graphics and document all procedures and code used for data cleaning and analysis.
-
Perform qualitative analysis of free-text responses, including codebook development, qualitative coding, and analysis using computer assisted qualitative data analysis software.
-
Develop and systematically apply data classification schemes and process and combine data sets for analysis from diverse sources.
-
Utilizes statistical software packages to manage, maintain and analyze large, complex statistical databases.
-
Present data by preparing charts, tables, and graphs, using software that can be used for scientific monographs, book chapters, and professional presentations (including poster and oral presentations).
-
Research methods in data analysis, revise study forms, graphically display analytic results, collaborate in writing or editing drafts of manuscripts for publication.
-
Provide a cross-tabulation, descriptive analysis using standard statistical procedures, rate standardization, stratification of data, and model building.
-
Recommend appropriate statistical techniques for analysis of research data and prepare statistical reports, analyze data, and use statistical software packages and programs such as SAS and R.
-
Implement and validate cutting-edge algorithms and new statistical methodologies to analyze diverse sources of data to answer research questions. Enters and verifies data fields and data dictionaries.
-
Transfer data between software, dataset creation (merge and concatenation), data cleaning (identify and correct data entry errors and missing values) and data transformation (create and categorize variables and impute data).
-
Check and confirm the accuracy of calculations conducted by collaborating programmers, analysts, and presenters to guard against mistakes in design, conduct, or presentation of risk estimates.
-
Collect and refine new data and refine existing data sources.
-
Create data entry applications to improve data collection and management.
-
Enhance data collection strategy and procedures for primary and secondary data sources, including recovered data sources such as scans and microfilms of paper archives.
-
Collects and analyzes mathematical data and performs descriptive and missing data analyses.
-
Perform data analysis of data sets involving statistical procedures varying in complexity from simple bivariate tests to advanced regression methods for longitudinal data analysis and time-to-event analysis; determine correlations between variables.
-
Perform data analysis including cross-tabulation, descriptive analysis using standard statistical procedures, as well as model building (logistic regression, conditional logistic regression).
-
Assist staff in conducting evaluations and analyses of programs using appropriate methods and tools and perform data management and carry out statistical analysis for assigned research projects.
-
Process and analyze data using blind-source separation techniques.
-
Organize, manage and design data files and plans for associated statistical analysis.
-
Tracks and documents all modifications, errors and changes to all databases and decisions.
-
Complete technical writing including co-authoring of articles for journal submission and writing of professional services agreements and statements of work.
-
Research and review literature to retrieve targeted clinical or scientific information from publicly available resources.
-
Transfer data between software and create datasets (merge and/or concatenation), data cleaning (identify and correct data entry errors and missing values) and data transformation (create and categorize variables and impute data).
-
Review literature and create bibliographies, research methods in data analysis, revise study forms, graphically display analytic results and collaborate with staff on writing and editing drafts of manuscripts for publication.
-
Research and review literature to retrieve targeted clinical or scientific information from publicly available sources such as PubMed and other sources.
-
Develops and coordinates the training program for staff in statistical and mathematical analysis.
-
Train staff in the laboratory to carry out data analyses and conduct applied analyses and interpretation and best practices.
-
Deliver lectures and other teaching activities on statistical topics for intramural researchers.
-
Write data analysis reports and participate in the preparation of scientific presentations and manuscripts.
-
Develop training strategies and implement training activities for internal and external researchers who are interested in using the data.
