Industrial/Organizational Product Science Intern | Fully Remote US

About the role

As an Industrial/Organizational (I/O) Product Science Intern, you will support the research, design, and testing of new assessments and assessment-related product features. You will work with Industrial/Organizational Psychologists and other internal teams to apply research within the Hirevue platform. Projects may include large language models, machine learning, simulations, conversational assessments, and other interactive assessment methods. This is a six-month internship beginning in August or September, with the possibility of extension. This role is a part-time internship, not exceeding 20 hours per week and does not involve direct customer interaction.

Essential Duties And Responsibilities

• Support the design, development, testing, and quality review of new assessments.
• Apply Industrial/Organizational Psychology, research, and data analysis skills to product projects.
• Assist with assessment content, scoring methods, prototypes, and AI-enabled features.
• Review research on selection and emerging assessment technologies, and help translate findings into product features.
• Support research on reliability, validity, fairness, subgroup differences, usability, and candidate experience.
• Serve as an expert evaluator by reviewing and rating the quality, accuracy, and effectiveness of assessment tools and technology-generated outputs.
• Collaborate with Industrial/Organizational Psychology, Product, and Data Science teams and share findings with technical and non-technical audiences.

Qualifications

• Currently enrolled in a Ph.D. program in Industrial/Organizational Psychology or a related field preferred.
• At least two years of graduate-level education in Industrial/Organizational Psychology or a related field preferred.
• Knowledge of personnel selection, psychometrics, statistics, research methods, or assessment development.
• Experience analyzing quantitative and qualitative data.
• Experience with assessment development, validation, or evaluation is preferred.
• Interest or experience in emerging assessment technologies, such as large language models, machine learning, natural language processing, prompt design, experimental design, or AI evaluation.
• Knowledge of EEO requirements, fairness, and professional guidelines for employee selection.