GDIT is hiring a mid-level Scientific Data Analyst to provide support to the Epidemiology Task Force: Ongoing COVID-19 Response Support. Due to the recent events caused by the COVID-19 pandemic, the CDC Epidemiology Task Force is responsible for identifying and tracking COVID-19 cases, spread and containment. The COVID-19 Epidemiology Task Force Response is critical to accomplishing the CDC’s mission and goals during the COVID-19 pandemic. This position will give support across several teams within the task force.
A scientific data analyst has the necessary education and work experiences to effectively provide data analysis, data management, and data visualization provide additional support to the task force.
RESPONSIBILITIES (vary with years of relevant experience and education):
Support study planning, protocol development, and study logistics, possibly including developing and keeping task trackers, protocol organization, organization of study documents (e.g. SOPs, forms, reports, etc.), and preparing study-related materials and overviews
Monitor data submissions from research study partners
Provide data cleaning and management support for research studies and surveillance platforms
Contribute to production of study/surveillance summaries or manuscripts for publication.
Ensure the security and confidentiality of analytical data files and provide data file documentation describing the scientific data source.
Coordinating or participating in routine study or surveillance meetings, possibly including taking study minutes and preparing materials on study progress.
Manage epidemiological and laboratory data by using SAS or equivalent statistical package (e.g. R)
Familiarity with data management software packages (e.g. R, REDCap, Microsoft Access, Excel, EpiInfo, STATA, etc.)
Conduct analyses including frequencies, longitudinal data analysis, and univariate and multivariate modeling techniques (linear regression, logistic regression, generalized linear models, and survival analysis)
Perform data quality assurance activities, including identifying and resolving any inconsistencies in data flow, data outside legitimate ranges, and illogical data responses by developing data quality reports and investigation and resolution of data anomalies or errors by using a combination of software packages including SAS or R, MS Access and Excel, and other software (e.g. REDCap)
Convert datasets from multiple different sources into SAS datasets
Manage data stored in a variety of file formats such as SAS datasets, Microsoft Access, Microsoft Excel, SQL, and ASCII files
Manipulate and transform data that are stored in a variety of file formats
Explore the use of data visualization platforms (e.g. R, Power BI, mapping software) to quickly summarize study findings
Support data visualization activities (both for hypothesis generation and to share data with the response) in order to develop communication materials such as data sets, slide sets and summary reports
Perform daily/weekly data runs and create daily/weekly reports
Trouble shoot issues with daily/weekly data runs
Work on ongoing basis to improve and automate code
Conducts weekly data cleaning and generate weekly error reports
Database management and upkeep as well as complete ad hoc data requests
Determine sampling methodologies to implement if case counts exceed certain thresholds, characterize surveillance back-fill to help with real-time interpretation of data
Determine how to best present age/sex/race adjusted estimates in daily/weekly reports, describe and work to minimize biases related to missingness of key variables such as race/ethnicity
Work with internal CDC staff/programs to push data to interactive public-facing website on weekly basis.
Compile individual-level data submitted from multiple external partners in diverse data formats and merge with laboratory testing results from CDC or contract laboratories
Track completeness and quality of data over time
Prepare summary tables and descriptive analyses of results on a regular basis
Have the necessary resources, skills, and materials to support the following data management lifecycle activities: execute the coordination of data entry processes, create data entry forms in software packages such as Microsoft Access and REDCap and perform data entry as required
Responsible for tracking of problem resolution related to data quality assurance activities by maintaining data-correction logbooks and/or files in order to improve the quality of the data collection/acquisition process
Create and modify SAS (or other) programs used for data management and create documentation for programs describing their functions and associated processes and output
Support the design, development, and implementation of surveillance tools to collect epidemiologic data
Communicate analytic results to internal CDC staff and external partners in a clear, concise and timely manner
Assist researchers in developing analytical programs in SAS or R and assist researchers in determining the appropriate statistical techniques to apply to their analyses
Required Skills and Experience
Bachelor’s degree with 5+ years of relevant experience
M.S. in statistics or mathematics with 3+ years of work experience
MPH with a concentration in Epidemiology or Biostatistics with 3+ years of work experience
Capable of fundamental programming SAS, R, SUDAAN, STATA or other statistical software for data analysis, survey data analysis, and data management
Desired Skills and Experience:
We are GDIT. The people supporting some of the most complex government, defense, and intelligence projects across the country. We deliver. Bringing the expertise needed to understand and advance critical missions. We transform. Shifting the ways clients invest in, integrate, and innovate technology solutions. We ensure today is safe and tomorrow is smarter. We are there. On the ground, beside our clients, in the lab, and everywhere in between. Offering the technology transformations, strategy, and mission services needed to get the job done.
GDIT is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, or any other protected class.