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Zscaler is seeking a Staff People Analytics Analyst to serve as the dedicated data science and research partner for the Recruiting organization. Based in San Jose with hybrid work (Tuesday-Thursday in office), you will partner directly with TA leadership as a trusted strategic consultant, translating complex talent data into actionable recruiting strategy.
You will not be an order-taker waiting for questions. Instead, you'll take a proactive research approach: digging into data to identify trends, flag bottlenecks before they escalate, and bring data-backed perspectives to leadership discussions. Your role bridges strategic analytics and hands-on execution.
Key responsibilities include:
- Partner with TA leadership to interpret talent data, craft strategic narratives, and prescribe solutions
- Lead proactive research into sourcing channel quality, interviewer effectiveness, market mapping, and recruiter capacity
- Field ad-hoc validation requests from TA leadership (e.g., candidate drop-off analysis) and scale them into self-serve insights
- Own and evolve the recruiting analytics stack, tracking funnel health, conversion rates, time-to-fill, and diversity metrics
- Build predictive hiring velocity and capacity forecasting models to align pipelines with headcount targets
You are data-driven, act like an owner, excel at problem-solving, champion simplicity in communication, and thrive in dynamic environments. You have a strong technical background in data science, quantitative research, or people analytics with proficiency in SQL, Python/R, and BI tools (Tableau, Looker, PowerBI). You understand recruiting workflows and ATS data structures (Greenhouse, Ashby, Workday). You demonstrate exceptional business acumen and consultative skills, with proven ability to translate complex data into strategic talent solutions. You're agile and manage competing priorities across infrastructure projects and immediate analytical needs. Preferred: experience designing self-serve predictive dashboards for TA leaders and developing hiring velocity models.
