Data hiring, evaluated like data work actually happens.
Data roles span analytics, engineering, and science — one generic interview loop can't cover all three. Recruitor matches every evaluation to a practitioner in that specific data discipline.
"Data" is three jobs wearing one job title.
One Title, Three Disciplines
Analytics, data engineering, and data science require overlapping but distinct skill sets — rarely tested as such.
SQL Screens Aren't Data Judgment
A syntax test says nothing about how a candidate reasons about messy, ambiguous data.
Discipline Confusion
An analytics-strong candidate can look weak in an engineering-framed interview, and vice versa.
Inconsistent Bars
Without a shared rubric per discipline, "strong data hire" means something different every time.
Domain-matched evaluators for each data discipline.
Discipline Identified
Your role is parsed to identify whether it's primarily analytics, engineering, or data science.
Practitioner Match
A working practitioner in that exact discipline conducts the evaluation.
Decision-Ready Report
A report scored against the right rubric for the right discipline — not a generic technical screen.
"The calibration bands are what sold me. A 'Senior' evaluation from Recruitor means the same thing whether it's Bangalore or Austin."