Data Analyst II - Center for the Study of Traumatic Stress (CSTS)

Join the HJF Team!

HJF is seeking a Data Analyst II to provide analytic and statistical support to a research project that will use advanced machine learning to predict suicide risk among active duty military service-members. The incumbent will support this research project by managing health and administrative data, running statistical models, and ensuring data quality and data integrity.

Project Summary: Researchers at Harvard Medical School and Uniformed Services University are collaborating on SAFEGUARD (Suicide Avoidance Focused Enhanced Group Using Algorithm Risk Detection) to develop multivariate models using health information and administrative data to identify active duty service-members at highest risk for suicidal behaviors and deliver targeted interventions to lower suicide risk.

The Center for the Study of Traumatic Stress (CSTS) is one of the nation's oldest and most highly regarded, academic-based organizations dedicated to advancing trauma-informed knowledge, leadership and methodologies. The Center's work addresses a wide scope of trauma exposure from the consequences of combat, operations other than war, terrorism, natural and human-made disasters, and public health threats as well as risk and protective factors associated with suicidal behaviors. CSTS is a part of our nation's federal medical school, Uniformed Services University (USU), and its Department of Psychiatry. These affiliations represent the Center's history, mission and future directions as a major contributor to our country's understanding of the impact of trauma and the advancement of trauma-informed care. Learn more about the CSTS.

The Department has active research programs in the Basic and Clinical Sciences and Neurosciences. In addition to intramural research projects, the Department maintains active research funded by the National Institute of Mental Health, National Institute of Drug Abuse, National Science Foundation, the Department of the Army and the Department of the Air Force. The department has ongoing collaborations with the Walter Reed Army Institute of Research, is sponsor of the Center for the Study of Traumatic Stress and provides psychiatry residency training through its affiliations with Walter Reed National Military Medical Center, National Naval Medical Center and Malcolm Grow Air Force Medical Center and the National Capital Area Graduate Medical Education Consortium.

The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF) is a nonprofit organization dedicated to advancing military medicine. We serve military, medical, academic and government clients by administering, managing and supporting preeminent scientific programs that benefit members of the armed forces and civilians alike. Since its founding in 1983, HJF has served as a vital link between the military medical community and its federal and private partners. HJF's support and administrative capabilities allow military medical researchers and clinicians to maintain their scientific focus and accomplish their research goals.

• Imports, cleans, transforms, validates, and/or builds datasets for research and training purposes.
• Assists in making data accessible to scientists, programmers, and other end users.
• Tests data to identify data integrity issues, making recommendations and coordinating with other analysts/data manager to plan solutions
• Troubleshoots problems concerning database records and communicates with co-workers and end users of the system.
• Makes recommendations and coordinates with other project data analysts/data managers to plan solutions.
• Links data from different sources by subject identifiers.
• Develops parsers to extract and transform data from JSON payloads originated from FHIR, HL7, or other health-care data standards.
• Runs statistical models against near real-time demographic and health information data to identify "high risk" soldiers.
• Recommends operating methods to improve processing, distribution, data flow, collection and database editing procedures.
• Writes code to construct the important variables / predictors of risk models and applies the coefficients from each of these models to calculate the outcome risk score.
• Creates weekly reports for the study team on recruitment (approach and consent rates) and check that the randomization is balanced at each site.
• Reviews survey data weekly for completeness and quality and be responsible for weekly reports on data quality to the study team.
• Reviews follow-up survey data for quality assurance and produce weekly reports on the response rate and quality of the follow-up data.
• Combines and standardizes data from various systems into a unified format for storage, analysis, and reporting.
• Ensures adherence to data governance, HIPAA regulations, and other relevant policies when handling sensitive health and administrative data.
• Performs other duties and responsibilities as assigned or directed by the supervisor, which may include attendance of and participation in required training for role.

Education and Experience

• Bachelor's Degree Required; Master's Degree Preferred. Preferably in Biostatistics, Statistics, Computer Science, Mathematics, or a related discipline.
• Minimum of 3-5 years experience required

Required Knowledge, Skills and Abilities

• Advanced knowledge in data cleaning and ETL techniques
• Strong proficiency in SQL for database querying, optimization, and management
  
• Strong proficiency in SAS
• Demonstrated expertise in Python, with the ability to perform data analysis, automation, and develop scripts for data extraction
• Experience with data modelling
• Must have strong Excel and SQL skills
• Ability to code in SQL, SAS, R, Python, and/or STATA software
• Ability to investigate data issues and participate in remediation activities
• Statistical and data analysis skills are a must to assist gathering and solving data quality issues
• Ability to review detailed documents to validate data in operating systems
• Experience in writing requirements
• Familiarity with healthcare data standards, including FHIR, ICD-10, and CPT codes
• Familiarity with military data sources preferred but not required
• Excel MACROS experience is a plus
• Experience with AWS services such as Redshift and S3 a plus
• Ability to obtain and maintain a T1/Public Trust background check

Work Environment

• This position will take place primarily in a office or clinical setting.

Compensation

• The annual salary range for this position is $64,200-$93,000/year. Actual salary will be determined based on experience, education, etc.

Benefits

• HJF offers a comprehensive suite of benefits focused on your health and well-being, from medical, dental, and vision coverage to health savings and retirement plans, and more.

Employment with HJF is contingent upon successful completion of a background check, which may include, but is not limited to, contacting your professional references, verification of previous employment, education and credentials, a criminal background check, and a department of motor vehicle (DMV) check if applicable. Any qualifications to be considered as equivalents, in lieu of stated minimums, require the prior approval of the Chief Human Resources Officer.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)

Any qualifications to be considered as equivalents, in lieu of stated minimums, require the prior approval of the Chief Human Resources Officer.