Senior Product Manager, AI / Data Classification

Zscaler•San Jose, CA

6d•Hybrid

About The Position

Zscaler is seeking a Senior Product Manager, AI / Data Classification to join their Data Protection team. This role will lead data classification capabilities within a Data Security platform, owning the end-to-end product strategy for discovering and classifying sensitive data across cloud, on-prem data stores, and SaaS applications. The goal is to turn classification outcomes into actionable risk reduction for security, privacy, and compliance teams. The role involves partnering with engineering, data science/ML, design, sales, and customer success to deliver accurate, scalable classification, clear policy outcomes, and measurable customer value. Responsibilities include owning the classification taxonomy, labeling standards, and policy model, driving accuracy improvements, setting requirements for enterprise-scale scanning, and defining how the platform combines various classification methods for structured and unstructured data.

Requirements

Product Management experience, with meaningful ownership of data security/privacy products. Product management experience can be substituted with data science experience
Demonstrated experience shipping products that use AI/ML and/or LLMs in production, with a strong understanding of data classification approaches across structured and unstructured data
Expertise in evaluation and quality measurement for classification systems and building/maintaining golden datasets
Ability to design human-in-the-loop workflows for high-stakes labels, covering review/approval, exception handling, and audit trails
Experience driving cost/performance tradeoffs for AI at scale, including token/compute budgeting, model selection, and managing latency for large corporations

Nice To Haves

Strong technical collaboration skills with ML engineering and data science
Familiarity with embedding-based similarity and semantic retrieval for classification and deduping (vector DBs, ANN indexing, chunking strategies)
Prior work in DSPM/DLP/CASB/insider risk where false negatives have high blast radius and you have designed processes to manage that risk

Responsibilities

Partner closely with a focused engineering, data science/ML, design, sales, and customer success to deliver accurate, scalable classification, clear policy outcomes, and measurable customer value
Own the classification taxonomy, labeling standards, and policy model (custom categories, confidence thresholds, inheritance, overrides, exceptions)
Drive accuracy improvements by managing precision/recall targets, sampling strategies, tuning workflows, and customer feedback loops
Set requirements for scanning at enterprise scale (billions of objects, large tables), optimizing cost, latency, and coverage
Define how the platform combines pattern-based detectors, NLP/ML, and LLM-assisted classification for structured and unstructured data