Epidemiologist – Randolph AFB, Texas

Location: Operational Support Team Aerospace Medicine Studies and Analysis, United States Air Force School of Aerospace Medicine, Joint Base San Antonio-Randolph, TX. U.S. citizenship required. Tier 1 Background Investigation required.

About the role

The Epidemiologist will provide support to Base Operational Support Teams in the field, oversee program development, data analysis, education, training, and field consultative support. The FESO branch supports embedded medical providers with evidence-based practices and a real-time data analytics dashboard of musculoskeletal and mental health risk down to the squadron level. Additionally, the FESO branch directs all aspects of an embedded Integrated Operational Support (IOS) training course held at USAFSAM.

Schedule

Normally 7:30 a.m. to 4:30 p.m., Monday through Friday. Occasional after-hours or weekend work may be required to support specific tasks, but the schedule will not exceed 40 hours per week.

Pay

Total compensation: $38.50 per hour.

Benefits

• Health, dental, and vision insurance
• Up to 80 hours of paid time off per year, available from day one
• Up to 56 hours of sick leave per year, available from day one
• Eleven paid federal holidays

Responsibilities

• Develop, retain, and provide expertise in the Aero-Medical Waiver Division's data processes to support interpretation and access to these databases.
• Create, maintain, validate, operate, and repair a data pipeline from the Aeromedical Waiver Division (AMWD) to a secure location in the Defense Health Agency (DHA) Application Virtualization Hosting Environment (AVHE), ensuring data quality, promptness, accessibility, compliance, and security.
• Assist in the development of investigation plans, determining feasibility and appropriateness based on data quality, quantity, and accessibility.
• Assist the AMWD in interpreting and accessing data products produced by the Analysis of Waiver Risk Evidence (AWARE) team, including publications, dashboard products, and data sets (when compliant with HIPAA and data use agreements).
• Perform validation and verification protocols to ensure pipeline products meet standards, and assist in corrections if models fail.
• Draft written communication for internal and external purposes.
• Participate and provide expert advice in interdisciplinary planning and analysis.
• Acquire necessary data access permissions to perform stated tasks.
• Use Air Force medical records systems and standards in job duties.
• Utilize relevant data repositories and collect data from various databases pursuant to agreements with owners.
• Provide conference support through active participation, preparation of posters/presentations, and publication of peer-reviewed manuscripts.
• Brief study findings at appropriate meetings or forums as determined by the Government.
• Provide technical automation support for Microsoft Windows, MS Office (Access, Excel, Publisher), MS SQL, and Adobe.
• Support data creation and administration for model development, analysis, and publication.
• Document computer code used for government review, approval, or replication, adhering to USAFSAM programming standards.
• Assist in briefings and document production to transfer knowledge of study products to customers in the AFRS and Air Force at large.

Requirements

• Master’s degree in epidemiology.
• Minimum of two years of experience in epidemiology.
• Current HIPAA training to access and process identified medical data.
• Advanced analytical skills in population health, health data surveillance, and visual analytics.
• Ability to design, conduct, and lead data analysis of operational studies on health surveillance data, military records, and risk reduction of negative health outcomes affecting the DAF total force population.
• Advanced skills in statistics, study design, and execution.
• Expertise in descriptive statistics and proficiency in SAS/SAS EG and SQL-related languages and software.
• Minimum of 5 years of experience using SAS/EG or SQL.

Qualifications (Desired)

• Experience within a health analytics-related field and working with DAF-related data.