Senior Analyst, Pricing Strategy & Operations

Job Description

Senior Analyst, Pricing Strategy & Operations | Confidential Employer

The Tone:
This is a hybrid role at Zscaler, a company that accelerates digital transformation by protecting customers from cyberattacks and data loss through its Zero Trust Exchange platform. The platform operates globally and is the world’s largest in-line cloud security platform. This role is crucial for driving data-backed pricing and monetization decisions within Zscaler’s SaaS business.

The TL;DR
• Role: Full Time
• Location: Hybrid

• Team: Reporting to the Manager, Pricing Strategy & Operations in the Product Management department.
• Mission: Drive data-backed pricing and monetization decisions for the SaaS business to support revenue growth and overall pricing effectiveness.
• Tech Stack: SQL, spreadsheets, reporting tools, AI tools, Salesforce, CPQ, Snowflake, Paradime, modern BI/reporting platforms.

What You’ll Actually Do
• Data Management: Own and maintain data tables, structures, and inputs necessary for pricing, packaging, discounting, cost, and product usage analysis, ensuring accuracy and reliability.
• Data Analysis: Analyze extensive datasets covering customers, products, usage, revenue, discounts, costs, and sales performance to identify trends, opportunities, and risks.
• Insight Translation: Convert complex data and analysis into clear, actionable insights that business stakeholders and executives can easily understand and utilize for decision-making.
• Reporting & Presentation: Create recurring and ad hoc reports, dashboards, and presentations to communicate pricing performance, product adoption, discounting trends, and monetization opportunities.
• Cross-functional Partnership: Collaborate with Product, Engineering, IT, Deal Desk, and Finance to ensure pricing guidance, cost inputs, product telemetry, and related data are accurately captured, maintained, and reflected in business systems.

The Must-Haves
• Background: Bachelor or Master’s degree in Business, Engineering, Statistics, Computer Science, or a related analytical field.
• Experience: 3–6 years of relevant experience in pricing analytics, business analytics, revenue analytics, strategy analytics, finance analytics, or sales/GTM analytics, with a foundational understanding of AI/ML technologies.
• Skills: Strong hands-on experience analyzing large datasets and generating business insights using SQL, spreadsheets, reporting tools, and AI tools, alongside proven ability to convert complex analysis into clear business recommendations and executive-ready presentations.
• Bonus: Practical experience leveraging AI predictive models or machine learning analytics workflows to optimize SaaS pricing models, price elasticity, or discounting strategy, deep functional experience in pricing, packaging, monetization, or revenue strategy, and prior experience in a global SaaS / enterprise software environment leveraging systems like Salesforce, CPQ, Snowflake, Paradime, and modern BI/reporting platforms.