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Salary
≈ $61k – $110k per year (Estimated)
Location
In office (Upper Marlboro)
Seniority
Junior · 2+ years exp

Confirmed on the employer's own hiring board on Oct 27, 2026. First seen by Alion on Oct 19, 2026. SAIC scores B on the Alion truth index.

Overview
Company
Impact
Profile match
SAIC delivers technology integration and mission services to government agencies. Its work spans enterprise information technology, space systems, engineering and digital modernisation. The company is one of the largest federal services contractors.

SAIC’s Identity and Data Sciences Lab (IDSL) team is seeking a Human Factors Engineer to assist with large-scale human-subjects testing of biometric and identity technologies. The IDSL performs unique test events to evaluate the performance of technologies such as face recognition, and other AI-based systems and to understand how optimize these systems for human workflows. As a Human Factors Engineer you will be responsible for tasks related to designing and executing tests, such as test design, the development of instructional materials, debrief surveys, as well as data review and annotation. The Human Factors Engineer will join the multi-disciplinary collaborative team at the IDSL.

Responsibilities:

  • Assist with development, administration, and analysis of surveys.
  • Assist with test planning and execution.
  • Support data collection activities with large groups of human subjects.
  • Develop briefing materials and signage for test events.
  • Review and annotate previously collected data and new incoming data in real time.

Required:

  • Bachelor’s degree and two years of experience in psychology, neuroscience, human factors or a related field or Master’s degree.
  • Must be able to obtain and maintain a DHS public trust requiring U.S. Citizenship.
  • Strong experience with human subjects testing.
  • Strong written and oral communication skills.
  • Experience developing and implementing experimental designs (e.g., randomized, blocked, or paired designs).
  • Experience with video review and annotation techniques (e.g., open coding).
  • Experience with quantitative and qualitative data analysis techniques.
  • Familiarity with statistical data analyses using R or Python.
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