Compensation Analyst – Customer Success (ZM181126FT)

Job Type: Full-time
Schedule: Monday to Friday, 8:30 am – 5:30 pm Pacific Time
Location: 100% Remote – Latin America
Start: As soon as possible

About the Company

A fast-growing US technology company that provides salary and compensation data to employees and employers is looking for a Compensation Analyst to join its Customer Success team.

About the Role

You will help the company's customers understand what the market is paying. Using the company's compensation data and intelligence, you will answer customer questions about pay benchmarks and how their compensation compares with their competitors.

Responsibilities

• Answer customer questions about market pay, salary ranges and total compensation using the company's data.
• Prepare clear compensation benchmarks and competitor comparisons for customers.
• Analyze compensation data in Excel and explain the findings in simple terms.
• Work with the Customer Success team to support and retain customers through calls, email and written reports.
• Use AI tools (Claude, ChatGPT) to speed up research and analysis.
• Keep customer notes and documentation up to date in Notion and Gmail.

Requirements

• Must have one of the following:
  • Experience as a Compensation Analyst or Total Rewards Analyst (or a similar compensation role), or
  • Customer Success experience at a compensation or salary-data company (e.g. Mercer, Radford / Aon, Willis Towers Watson, Payscale, Salary.com, Pave, Carta).
• Advanced English (C1 or higher), written and spoken.
• Strong Excel skills and comfort working with data.
• Excellent attention to detail.
• Confident on the phone and on video calls with customers.
• Available full time, 8:30 am – 5:30 pm Pacific Time.

Nice to Have

• Experience with US compensation, pay benchmarking or salary surveys.
• Experience with Notion and AI tools such as Claude or ChatGPT.
• Experience working with US clients or a US tech company.

What We Offer

• 100% remote, full-time position with a US company.
• Long-term opportunity in a growing team.
• Training and support on the company's tools and data.