Principal People Scientist, People Strategy & Analytics
Capital One
- Location
- McLean, VA
- Work model
- On-Site
- Level
- Principal
- Posted
- Aug 17, 2026
Skills
About this role
Principal People Scientist, People Strategy & Analytics The People Strategy and Analytics team at Capital One is on a mission to transform the associate experience – from hiring to onboarding to career development – so that all talent can flourish. As a Principal People Scientist on the People Strategy & Analytics team, you will use organizational science, measurement techniques, behavioral insights, and advanced analytics to help drive that transformation. Our ideal candidate will display a strong balance of analytical and problem solving skills, business consulting, and communication competencies, as well as the ability to work in a dynamic team environment. You’ll be on a cross-functional team that includes analysts, data scientists, and other people scientists. This role will primarily specialize in enterprise listening strategies like surveying & measurement design, but will also have frequent opportunities to collaborate with key HR partners in areas like Talent & Performance Management, People Leadership and Diversity, Inclusion, & Belonging. Projects will focus on improving the associate experience and unlocking best practices in the talent strategy space. A typical day will include client consultation, measurement design, program design, insights generation, and analysis. Your main responsibilities include, but are not limited to: Consultation: Bring your expertise in organizational science principles and analysis to help our clients frame problems, answer questions, and design solutions to improve the associate experience Design : Build and drive key programs and solutions for our partners, including strategies for measurement and validation Experimentation : Partner with clients and teams across Capital One to design experiments to understand key drivers of associates and behavior Insights & analysis : Analyze the impact of our programs and combine those insights with the latest thinking in organizational science to help our clients make data-driven, informed decisions Successful team members demonstrate competencies in these areas: Purpose : You feel a deep personal connection to improving the associate experience and are motivated by applying organizational science in a mission-driven way Analytical thinking : A proven track record of decision making and problem solving based in analytics. Conceptual thinking skills must be complemented by a strong quantitative orientation. Identify opportunities for improvement and use data to make strategic and tactical recommendations. Execution : Develop and test hypotheses, design solutions, assess operational feasibility, support implementation efforts, and develop plans and tools for monitoring outcomes Partnership : Collaborate effectively with other team members and HR clients Business communication : Strong written and oral communication skills, including visualization skills (i.e., able to “tell the story” and highlight key insights in a clear and concise manner that is easily understood by stakeholders) Results focus : Drives for results and achieves important goals; applies strong organizational skills and detail orientation, even amidst ambiguity Basic Qualifications: Master's degree At least 1 year of professional work experience in Industrial and Organizational Psychology OR Organizational Behavior OR Behavioral Science At least 1 year of data analysis experience conducting analyses, and building statistical models in R, Python, or SQL At least 2 years of experience in consulting with external or internal clients across a variety of seniority levels and technical experience Preferred Qualifications: PhD in Industrial and Organizational Psychology or Organizational Behavior or Behavioral Science At least 2 years professional work experience in Industrial and Organizational Psychology or Organizational Behavior Knowledge of advanced statistical methodologies, including regression, or longitudinal analysis, or Bayesian modeling At this