Statistician

Statement of Work Details

Performs experimental investigations and similar research projects utilizing extensive applications of mathematical and statistical methodologies.

• Perform statistical analysis using novel methods and algorithms. 1
• 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. 2

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. 3
• 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 manuscript for publication.
• Implement and validate cutting-edge algorithms and new statistical methodologies to analyze diverse sources of data to answer research questions. 4

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.
• Create data entry applications to improve data collection and management.

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.

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 agreement and statements of work.
• Research and review literature to retrieve targeted clinical or scientific information from publicly available resources.
• 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. 5

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.
• 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.

Deliverables

• Work products and documents related to applying existing statistical and machine learning methods in application projects e.g. classification and regression models deep learning decision forests - Daily
• Work products and documents related to developing new statistical or machine learning techniques in response to NIMH researcher needs including statistical modelling of complex neural imaging and behavioral data collected in internal experiments Daily
• Work products and documents related to providing consulting and support activities to NIMH researchers employing statistical and machine learning techniques Daily
• Work products and documents from software engineering efforts to package new or existing machine learning methods into open-source code usable by NIMH or external researchers. - Ad-Hoc
• Research papers about novel techniques developed by the contractor as first author - Ad-Hoc
• Research papers about collaboration projects with NIMH IRP research groups resulting from development and support activities as co-author Ad Hoc
• Work products and documents related to developing and delivering educational material on statistical or machine learning techniques - Ad-Hoc