Compensation Analyst (AI)

TL;DR

Compensation Analyst (AI): Supporting customers in implementing and extracting value from a real-time compensation intelligence platform with an accent on data mapping, validation, and customer education. Focus on analyzing complex compensation datasets, optimizing system configurations, and developing data-driven insights.

Location: Hybrid: Must be based in or near Orange County (Irvine), Denver, or San Francisco

Salary: $95K – $115K • Offers Equity

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A venture-backed AI startup providing real-time compensation intelligence to leading enterprise hirify.globalnies like NVIDIA, Stripe, and OpenAI.

What you will do

• Partner with new customers to interpret compensation data and map it into the platform to accelerate time-to-value.
• Analyze and validate customer data to troubleshoot issues and ensure accuracy.
• Collaborate with product and support teams to resolve complex data challenges and optimize system performance.
• Deliver demos and trainings to educate customers on how the platform solves compensation challenges.
• Identify trends and develop research, blog posts, and guides based on the hirify.globalny's data network.

Requirements

• 1+ year of experience in compensation total rewards, Human Resource analytics, or People Systems.
• Familiarity with compensation benchmarking and a sound understanding of base, incentives, and equity.
• Proficiency in data tools such as Excel or Google Sheets.
• Strong written and verbal communication skills for technical and advisory customer interaction.
• Comfort working with HR technology systems and ability to explain complex topics clearly.

Nice to have

• 2+ years of experience in compensation or HR analytics.
• Advanced data analysis skills with SQL or Python.
• Experience creating educational content such as reports, guides, or articles.
• Solid understanding of designing and configuring systems for engineering teams.

Culture & Benefits

• Equity options as part of the compensation package.
• Culture of transparency, ownership, and continuous learning.
• Collaborative, curious, and driven team environment.
• Hybrid work model prioritizing in-person collaboration at HQ or regional offices.