Human Factors Engineer — Biometric & AI Testing

SAIC; Upper Marlboro (MD); On-site; USD 85,000 - 110,000; Full time

Job summary

SAIC's Identity and Data Sciences Lab (IDSL) seeks a Human Factors Engineer to design and execute large-scale human-subjects tests of biometric and identity technologies. You will develop surveys, plan tests, and annotate data to understand and optimize AI-based systems for human workflows.

Collaboration across a multidisciplinary team is expected, with focus on rigorous experimental design and data analysis.

Qualifications

• 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.

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.

Skills

Human factors

Surveys

Test planning

Data collection

Data annotation

Experimental design

Open coding

Qualitative analysis

Quantitative analysis

Education

Bachelor's degree in psychology, neuroscience, human factors or related field

Master's degree in a related field

Tools

R

Python

Job description

SAIC's Identity and Data Sciences Lab (IDSL) seeks a Human Factors Engineer to design and execute large-scale human-subjects tests of biometric and identity technologies. You will develop surveys, plan tests, and annotate data to understand and optimize AI-based systems for human workflows.

Collaboration across a multidisciplinary team is expected, with focus on rigorous experimental design and data analysis.