Statistician Data Analyst And Programmer

Location

Rockville, MD | United States

Job description

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Axle is seeking a Statistician Data Analyst And Programmer to join our vibrant team at the National Institutes of Health (NIH) supporting the National Institute on Minority Health and Health Disparities (NIMHD) located in Rockville, MD.

Benefits We Offer:

• 100% Medical, Dental & Vision Coverage for Employees
• Paid Time Off and Paid Holidays
• 401K match up to 5%
• Educational Benefits for Career Growth
• Employee Referral Bonus
• Flexible Spending Accounts:
  • Healthcare (FSA)
  • Parking Reimbursement Account (PRK)
  • Dependent Care Assistant Program (DCAP)
  • Transportation Reimbursement Account (TRN)

Overall Position Summary and Objectives

​ Under this task order, the contractor will independently provide epidemiologic and statistical services to satisfy the overall operational objectives of the NIMHD Division of Intramural Research. The primary objective is to provide services and deliverables through the performance of support services. We are seeking one full-time statistician/data analyst/programmer to support the research activities of the NIMHD Division of Intramural Research.

Deliverables:

• ​ Provide expertise/advice on advanced study design, statistical analysis, and data presentation methods - Ad-Hoc
• Run Validation - Ad-Hoc
• Meet with lab members to present updates - Ad-Hoc
• Develop and implement methods and procedures for the collection, processing, compilation, cleaning, and analysis of data in collaboration with DIR investigators and research fellows - Ad-Hoc
• Perform data cleaning, formatting, variable recoding, data harmonization, and data quality checks, and data management and manipulation - Ad-Hoc
• Perform statistical analyses of large, complex datasets, preferably using SAS, for population health research using existing NIH and publicly available datasets or data collected by NIMHD investigators - Ad-Hoc
• Prepare for publication, results from clinical trials, intervention studies, observational studies, and secondary data analysis projects using complex survey data, hospital/medical records, administrative data, or other data sources - Ad-Hoc
• Interpret and communicate results of analyses in written and oral formats - Ad-Hoc
• Generate tables and graphics for scientific abstracts, manuscripts, and presentations - Ad-Hoc
• Prepare and/or update data tables and figures, methods sections of manuscripts, reports, and other documents for presentation and/or publication - Ad-Hoc
• Manage the storage,sections of manuscripts, reports, and other documents for presentation and/or publication - Ad-Hoc
• Manage the storage, tracking, internal control, and retrieval of information, data documentation, and datasets for all assigned projects - Ad-Hoc
• Attend research-related and statistical consultation meetings as requested by the senior biostatistician, and DIR investigators and research fellows; and Report, either verbally and/or in writing, regular updates on the progress of their work - Ad-Hoc
• Working with the NIMHD DIR investigators and trainees to perform data management and data analysis for both primary data collection studies and secondary/publicly available datasets - Ad-Hoc
• Perform other duties as assigned. This job description is not designed to cover or contain a comprehensive list of duties or responsibilities that are required of the candidate for this job. Duties and responsibilities may change at any time with or without notice depending on the studies in the lab. - Ad-Hoc
• Conduct statistical analyses; perform data cleaning and formatting, data harmonization, and data analyses; and prepare results for publication from intervention studies, observational studies, and secondary data analysis projects using complex survey data, hospital/medical records, administrative data, or other data sources - Ad-Hoc
• Conduct data collection/entry, management, cleaning, and manipulation activities - Ad-Hoc
• Prepare and/or update data tables and figures, methods sections of manuscripts, reports, and other documents for presentation and/or publication - Ad-Hoc
• Attend all lab meetings, lab check-ins, and other research-related meetings as requested by investigators or trainees - Ad-Hoc
• Attend all lab meetings, lab check-ins, and other research-related meetings as requested by investigators or trainees - Ad-Hoc
• Train trainees on developing statistical analytic codes to analyze quantitative data to achieve research objectives - Ad-Hoc
• Provide periodic training on contemporary epidemiological and biostatistics analytics approaches to the NIMHD DIR - Ad-Hoc

Work Details:

• Perform advanced epidemiologic and statistical analyses suitable for studies of health disparities and minority health including (but not limited to): linear and non-linear regression modeling; survival analysis; time series analysis; propensity score matching, weighting, standardization, multiple imputation, missing data weighting, censor weighting, and small area estimation to account for confounding, missing data, loss to follow up, selection bias, and other forms of potential bias in studies 1
• Perform data programming, analysis and presentation by preparing charts, tables and graphs using software such as R, SAS and STATA. 2
• Conduct statistical analyses; perform data cleaning and formatting, data harmonization, and data analyses; and prepare results for publication from intervention studies, observational studies, and secondary data analysis projects using complex survey data, hospital/medical records, administrative data, or other data sources. 3
• Prepare and/or update data tables and figures, methods sections of manuscripts, reports, and other documents for presentation and/or publication. 4
• Take lead of the storage, tracking, internal review, and retrieval of information, documentation, and datasets for all assigned projects and projects of any subordinates. 5
• Performs experimental investigations and similar research projects utilizing extensive applications of mathematical and statistical methodologies.
• Perform statistical analysis using novel methods and algorithms.
• Assist researchers with the planning, implementing, and analysis of research projects.
• 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.
• 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.
• Conduct statistical analyses; perform data cleaning and formatting, data harmonization, and data analyses; and prepare results for publication from intervention studies, observational studies, and secondary data analysis projects using complex survey data, hospital/medical records, administrative data, or other data sources
• Advanced epidemiologic and statistical methods suitable for studies of health disparities and minority health including (but not limited to): linear and non-linear regression modeling; survival analysis; time series analysis; propensity score matching, weighting, standardization, multiple imputation, missing data weighting, censor weighting, and small area estimation to account for confounding, missing data, loss to follow up, selection bias, and other forms of potential bias in studies
• Design and conduct statistical analyses using complex survey data or other secondary data sources that involve sampling weights (e.g., NHANES, BRFSS, National Health Interview Survey [NHIS], Medical Expenditure Panel Survey [MEPS], Current Population Survey and various supplements)
• Meet with data customers inside and outside the DIR to assess dataset requirements.
• Perform statistical analyses of large, complex datasets, preferably using SAS, for population health research using existing NIH and publicly available datasets or data collected by NIMHD investigators.
• 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.
• 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.
• 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.
• Develop and systematically apply data classification schemes and process and combine data sets for analysis from diverse sources.
• Design and conduct statistical analyses using hospital/medical records, administrative data, and other primary and secondary data sources
• Design and analyze studies using high-dimensional, longitudinal, clustered, multi-level, and repeated measures data
• Design and conduct statistical analyses using complex survey data or other secondary data sources that involve sampling weights (e.g., NHANES, BRFSS, National Health Interview Survey [NHIS], Medical Expenditure Panel Survey [MEPS], Current Population Survey and various supplements).
• Develop and implement methods and procedures for the collection, processing, compilation, cleaning, and analysis of data in collaboration with DIR investigators and trainees.
• Utilizes statistical software packages to manage, maintain and analyze large, complex statistical databases.
• 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.
• Generate tables and graphics for abstracts, manuscripts, and presentations
• Prepare for publication, results from clinical trials, intervention studies, observational studies, and secondary data analysis projects using complex survey data, hospital/medical records, administrative data, or other data sources.
• Interpret and communicate results of analyses in written and oral formats.
• 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.
• Conduct data collection/entry, management, cleaning, and manipulation activities.
• Creates Data Wokflow 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 datasets.
• Analyze studies using high-dimensional, longitudinal, clustered, multi-level, and repeated measures data.
• Clean, condense, merge, and reformat data into files that are appropriate for data analysis and data sharing, including preparing de-identified datasets and documentation for external users
• Create variables as needed for analyses and document methods and definitions for all variables created (e.g., data dictionary)
• 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.
• Perform data cleaning, formatting, variable recoding, data harmonization, and data quality checks, and data management and manipulation
• 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
• Develops and coordinates the training program for staff in statistical and mathematical analysis.
• Attend all lab meetings, lab check-ins, and other research-related meetings as requested by investigators or trainees.
• Report, either verbally and/or in writing, regular updates on the progress of their work to investigators.
• Provide expertise on epidemiologic and statistical research methods as needed for research projects, protocols, and proposals
• Train trainees on developing statistical analytic codes to analyze quantitative data to achieve research objectives and interpreting results from different statistical analyses
• Provide periodic training on contemporary epidemiologic and biostatistics analytics approaches to the NIMHD DIR.

1, 2, 3, 4, 5 represents priority rankings, where 1 is highest priority and 5 is lowest priority of those ranked

Minimum Education

Master's

Additional Qualifications:

Certifications & Licenses

• Doctorate degree in Biostatistics, epidemiology, statistics, or a closely related field
• Applicants with publications in peer reviewed Journals are preferable
• Preferred candidates with Health Disparities research experience

Field of Study

• Statistics and Decision Science
• Computer Programming and Data Processing
• Applied Mathematics
• Management Information Systems and Statistics
• Mathematics and Computer Science

Software

• MPlus
• SUDAAN
• ArcGIS
• R
• SPSS
• Python
• SAS
• STATA
• C++

Skills

• Scientific Data analysis
• Statistical modelling
• Algorithm development
• Data visualization
• Machine learning
• Proficiency in using advanced statistical methods
• Linear and non-linear regression
• Expertise to perform the duties of the position, which include working with NIMHD DIR investigators and fellows to perform data management and data analysis for both primary data collection studies and secondary/publicly available datasets in a timely manner
• Experience conducting statistical analyses in complex survey data or other secondary data sources that involve sampling weights (e.g., NHANES, National Health Interview Survey [NHIS], Medical Expenditure Panel Survey [MEPS])
• Experience with structural equation modeling, including but not limited mediation analysis, effect measure modification, moderated mediation analysis, latent class analysis (LCA), principal components analysis (PCA) and other dimensionality reduction methods (structural equation modeling); non-parametric statistical methods; quasi-experimental statistical analyses (e.g., difference-in-difference)
• Analyze studies using high-dimensional, longitudinal, clustered, multi-level, and repeated measures data
• Familiarity with Bayesian statistics and simulation modeling
• Experience in working with students or trainees in teaching data analytic skills
• Clean, condense, merge, and reformat data into files that are appropriate for data analysis and data sharing, including preparing de-identified datasets and documentation for external users
• Create variables as needed for analyses and document methods and definitions for all variables created (e.g., data dictionary)
• Expertise in performing statistical analyses using multiple statistical analysis software packages
• Excellent analytical, organizational, and time-management skills
• A drive to learn and master new technologies, statistical methods, and techniques
• Experience conducting statistical analyses in electronic health records (EHR/EMR) and administrative claims
• Data cleaning
• Data analysis
• Epidemiology
• Data mining

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: [email protected]

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