People Scientist

Roblox
San Mateo, CA, United StatesPosted 26 March 2026

Job Description

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The People Science Analytics team at Roblox supports our People, Places and Systems organization in optimizing the complete talent lifecycle. We combine behavioral science and rigorous research methods to guide decisions related to hiring, capability development, performance, and organizational effectiveness. Our team delivers a wide range of insights and solutions for Roblox, from developing hiring assessments and conducting job analysis to executing workforce research and shaping people practices across the company. In this role you will apply industrial-organizational psychology principles to strengthen the systems, processes, and programs that shape how we hire. You will use job analysis, competency modeling, program evaluation techniques, and evidence-based research methods to ensure our selection practices are structured, fair, and aligned with role requirements. You will directly contribute to the design, refinement, and maintenance of company-wide recruiting programs and processes, helping ensure they operate with consistency and scientific rigor. Your work will inform how hiring criteria are defined, how that criteria is evaluated, and how we maintain standardized practices at scale. Reporting to the Manager of People Science, you will be embedded within the Recruiting Programs team and partner closely with program leaders, recruiters, and hiring teams. In this matrixed role you will bring scientific rigor to the development and ongoing improvement of recruiting programs while remaining connected to the broader People Science discipline and team. This role is based onsite at our HQ in San Mateo, CA. You Will : Serve as an embedded People Science partner to the Recruiting Programs team, providing evidence-based consultation. Apply industrial-organizational psychology principles to design, evaluate, and maintain companywide recruiting programs and selection processes. Define and curate the systems, frameworks, and guidance that support structured interviews and consistent evaluation practices. Conduct job analyses and role research, including directly interviewing and engaging with software engineers and engineering leaders to establish job-relevant criteria, competencies, and evaluation signals. Evaluate the effectiveness, consistency, fairness, and potential adverse impact of selection practices using applied research and program evaluation methods. Partner with the People Data Science team to generate meaningful insights into hiring programs using quantitative and qualitative data. Analyze quantitative and qualitative hiring data to identify patterns and inform continuous improvement. Guide the development and ongoing improvement of interviewer training materials. Communicate insights and recommendations through clear documentation, tools, and presentations that support adoption at scale. You Have : PhD in Industrial-Organizational Psychology or a closely related discipline. Two to four years of applied experience supporting selection systems, hiring programs, or organizational research in a corporate setting. Strong grounding in job analysis, competency modeling, and evidence-based selection design. Experience evaluating or suppor ... (truncated, view full listing at source)
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