Vast Staff People Analytics Partner at Vast responsible for building the People Analytics function from the ground up. Delivers data audits, attrition modeling, and performance analysis to support talent decisions.
Responsibilities
Build the foundation
Lead a full audit of People data quality, completeness, consistency, and governance
Partner with Information Systems on a unified People data model that becomes the single source of truth
Define standard People metrics and KPIs, with clear definitions, calculation logic, and documentation
Deliver insight leaders act on
Build attrition and flight-risk models and turn the findings into practical retention strategies
Analyze what drives hiring outcomes, retention, performance, and engagement
Evaluate People programs and policies with rigorous methods, including causal inference where it fits
Support pay equity reviews, market benchmarking, and merit and promotion modeling
Build workforce planning and headcount forecasting models
Make data self-service
Design and maintain Quarterly Business Review (QBR) dashboard for executives (ex: Tableau dashboards for headcount, hiring funnel, attrition, compensation, performance, learning, and engagement.)
Qualification
Bachelors in Statistics8+ years in PeopleAdvanced SQLAdvanced TableauStrong applied statisticsMasters or PhD in StatisticsSurvival analysisPay equity and compensation modelingModern ELT tools (FivetranFamiliarity with EEO-1
Required
Bachelors in Statistics, I/O Psychology, Economics, Data Science, or a related field
8+ years in People, Workforce, or HR Analytics, or a closely related quantitative role
Advanced SQL, including data modeling and data quality auditing
Hands-on experience in a data warehouse (Snowflake, BigQuery, Redshift, or Databricks)
Advanced Tableau, including dashboards built for leadership audiences
Strong applied statistics, including regression and inferential methods
Experience building attrition or retention models
Experience handling confidential employee data
A track record of influencing senior stakeholders with clear recommendations
Preferred
Masters or PhD in Statistics, I/O Psychology, Economics, Data Science, or a related field
Survival analysis, multilevel or longitudinal models, or Bayesian hierarchical modeling
