We’re looking for an experienced Manager of People Analytics to join our people analytics function. Our team uncovers data-driven insights to better attract, develop, motivate, and retain Meta’s most important asset – our people.
As part of the Global Talent Selection team, you will serve as a strategic partner with Recruiting, HR, Business, and Product leadership to deliver selection solutions — including the design, development, and implementation of talent acquisition and hiring programs. You’ll help shape the strategy around assessment design and validation, program evaluation, and candidate experience as well as help develop and refine people processes and technology to make an exceptional workplace even better.
We are looking for someone who has excellent communication, collaboration, and interpersonal skills, and can effectively lead a team of I-O psychologists from both a technical and people leadership perspective. The ideal candidate will have a proven track record in managing and developing a high performing team, developing strengths of individual contributors, partnering across teams, deep knowledge of selection concepts and related I-O areas, and a good understanding of processes related to hiring programs.
People Analytics Manager, Global Talent Selection
Responsibilities
- Lead a team of I-O psychologists and people research scientists ensuring the team is productive, engaged, and thriving in their career
- Collaborate effectively with and mentor other team members
- Partner with Recruiting, HR, and Meta leadership and team members to identify opportunities for selection research and best practices to drive scalable, strategic assessment decisions, programs and process developments
- Execute, guide, and/or support selection assessment and selection technology-oriented research
- Partner with cross-functional teams to identify and clarify critical people, process and programmatic selection system issues and develop solutions to resolve
- Bring together Meta-specific data and outside research to help leaders understand people and selection issues
- Communicate statistical analyses and results, along with implications, to technical and non-technical audiences, to include varying levels of leadership
- Provide technical expertise to team members to guide assessment development and programmatic implementation design and statistical analyses
- Collaborate effectively with the Compliance and Employment Law team on a variety of sensitive projects
- Demonstrate exceptional judgment and discretion when dealing with highly sensitive people data and business issues
- Develop knowledge of recruiting and hiring processes and strategies at Meta
Minimum Qualifications
- PhD in Industrial-Organizational Psychology
- 5+ years of internal or external consulting experience in assessment development, human resources, program evaluation, or a related field
- Experience managing a team of I-O consultants or researchers
- Psychometric assessment development experience
- Experience with validating and implementing assessments (e.g., compensatory modeling, criterion-related validity study)
- Proficiency leveraging software tools such as SQL and Python to manage structured and unstructured data sets
- Experience managing and analyzing data using tools such as SPSS, R, or similar tools and experience troubleshooting others' analyses and code
- Experience communicating research findings and selection best practices to audiences with varying levels of technical knowledge
- Openness to feedback and self awareness skills
- Coaching and people development skills
Preferred Qualifications
- 3+ years experience working internally within a medium to large organization with professional employees (e.g., high-tech, financial services, healthcare, biotech)
- Experience developing and leading the development and implementation of advanced psychometric assessments (e.g., structured interviews, simulations)
- Experience developing and leading the development and implementation of scalable assessment programs (e.g., situational judgment tests, structured interviewing)
- Experience applying statistical methods (e.g., linear regression, ANOVA) and quasi-experimental research or causal inference techniques
- Experience leading and managing team members who are not co-located
