Data Scientist

Organization
U.S. Department of Defense (DOD)
Reference Code
DHA-2019-0001R
How to Apply

Components of the online application are as follows:

  • Profile Information
  • Educational and Employment History
  • Essay Questions (goals, experiences, and skills relevant to the opportunity)
  • Resume (PDF)
  • Transcripts/Academic Records
  • Recommendation

Submitted documents must have all social security numbers, student identification numbers, and/or dates of birth removed (blanked out, blackened out, made illegible, etc.) prior to uploading into the application system.

If you have questions, send an email to orisedod@orise.orau.gov. Please list the reference code of this opportunity in the subject line of the email.

All documents must be in English or include an official English translation.

Description

The Defense Health Agency (DHA) is a joint, integrated, Combat Support Agency that enables the Army, Navy, and Air Force (AF) medical services to provide a medically ready force and ready medical force to Combatant Commands (COCOM) in both peacetime and wartime. The DHA supports the delivery of integrated, affordable, and high quality health services to Military Health System (MHS) beneficiaries and is responsible for driving greater integration of clinical and business processes across the MHS.  The Health Information Technology (HIT) Directorate is responsible for the development of plans, programs, and procedures to support worldwide medical service missions as well as identifying shortfalls within current program plans and budget in order to field new technologies and services. The Solution Delivery Division (SDD) provides support to the DoD population health data systems that enhance the quality, efficiency, effectiveness of healthcare services, and access to information to aid health care teams improve such services.

The objective of this fellowship is to participate in the collection and analysis of MHS health data, using accepted Data Science Techniques in population health studies, disease prevention, managed care, medical readiness, health promotion, clinical preventive services, customer service, and service related data analysis. The fellow will also research and collaborate in providing actionable Business Intelligence (BI) and decision support data to the DHA and the beneficiaries of the DHA, as well as the Military Service Surgeons General, and Senior Department of Defense Officials. This fellowship will support the MHS and DHA in developing process improvement measures as they implement population-based healthcare, including working with Health Plan Employee Data and Information Set measures, the National Committee for Quality Assurance (NCQA), the Military Health System Population Health Portal (MHSPHP), and Individual Medical Readiness (IMR) requirements. This fellowship will provide an opportunity to work with a broad range of technical health data related to population studies, disease prevention, managed care, medical readiness, health promotion, clinical preventive services, customer service, and other highly complex, highly technical health service related data analysis, BI and decision support.

Appointment Length

This appointment is a twelve month research appointment, with the possibility to be renewed for additional research periods. Appointments may be extended depending on funding availability, project assignment, program rules, and availability of the participant.

Participant Benefits

Participants will receive a stipend to be determined by DHA. Stipends are typically based on the participant’s academic standing, discipline, experience, and research facility location.  Other benefits may include the following:

  • Health Insurance Supplement. Participants are eligible to purchase health insurance through ORISE.
  • Relocation Allowance
  • Training and Travel Allowance

Nature of Appointment

The participant will not enter into an employee/employer relationship with ORISE, ORAU, DOD, or any other office or agency.  Instead, the participant will be affiliated with ORISE for the administration of the appointment through the ORISE appointment letter and Terms of Appointment.

While participants will not enter into an employment relationship with DOD or any other agency, this opportunity will require a suitability investigation/background investigation. Any offer made is considered tentative pending favorable outcome of the investigation.

Qualifications

A Minimum of a Masters’ degree in Public Health, Health Services Research, Epidemiology, Biostatistics, Statistics, Nursing Informatics, or previous participation in the program as an Oak Ridge Institute for Science and Education (ORISE) Fellow is required.

Preferred experience in the following areas:

  • Analyzing quality improvement data
  • Experience in data mining and text mining and large-scale data management
  • Experience conducting statistical analysis, including applying multivariate regression methods and building predictive models involving health data
  • Developing and deploying clinical performance metrics using BASE SAS or similar systems
  • Experience with Microsoft Management Studio SQL Server; Microsoft Visual SQL Server Integration Services; SAS BI or other similar Business Analytics Software package; R or Python Programming Languages

Security Requirement: Participant must be able to receive a favorable adjudication for Tier III Position of Public Trust investigation at the time of the fellowship.

Eligibility Requirements
  • Citizenship: U.S. Citizen Only
  • Degree: Master's Degree or Doctoral Degree received within the last 60 months or currently pursuing.
  • Overall GPA: 3.00
  • Discipline(s):
    • Communications and Graphics Design (2 )
    • Computer, Information, and Data Sciences (16 )
    • Earth and Geosciences (20 )
    • Engineering (27 )
    • Environmental and Marine Sciences (15 )
    • Life Health and Medical Sciences (46 )
    • Mathematics and Statistics (11 )
    • Nanotechnology (1 )
    • Other Non-S&E (2 )
    • Other Physical Sciences (12 )
    • Physics (16 )
    • Social and Behavioral Sciences (27 )