Compensation Partner

চাকরির বিবরণ

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy .

AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.

The Compensation Partner is a core member of Gusto's People team, supporting compensation programs that help us attract, retain, and reward top talent. This role is the operational engine of the compensation function: the person who makes sure our programs run accurately, on time, and consistently for every Gustie.

দায়িত্ব

• Support the execution of Gusto's compensation programs and cycles, including merit, promotion, and equity refresh, handling data preparation, validation, tracking, and follow-through.
• Serve as a first point of contact for compensation questions from HRBPs, recruiters, and managers, resolving requests and escalating the ones that need extra attention.
• Manage annual compensation cycles (merit, equity refresh, benchmarking) from data collection through communication.
• Conduct job matching and market benchmarking using survey data (Radford/Aon, Mercer, Pave) and prepare recommendations on pay ranges and offer positioning for review.
• Model and prepare new hire, promotion, and internal transfer recommendations against approved bands and internal equity comparisons.
• Maintain compensation data integrity across Workday, Pave, and our compensation bands, running recurring audits and reconciling discrepancies before they reach downstream processes.
• Prepare recurring reports and dashboards on pay positioning, band utilization, and cycle progress, and produce ad hoc analysis for partners across People and Finance.
• Use AI tools and automation to take manual work out of recurring analysis, audits, and reporting, with sound judgment about when output needs to be validated.
• Support compliance with federal, state, and local pay regulations, including pay transparency postings, FLSA classification reviews, and annual survey submissions.
• Document and improve compensation processes so that the work is repeatable, auditable, and not dependent on any one person's memory.

যোগ্যতা

• 3+ years of experience in Compensation, Total Rewards, People Operations, or a related analytical function - ideally in a high-growth technology environment.
• AI fluency: hands-on experience using AI tools to accelerate analysis, research, or documentation, paired with good instincts about when to trust and when to verify.
• Strong analytical foundation: advanced spreadsheet skills (Excel, Google Sheets) including lookups, pivots, and formula-driven models, and the ability to spot when a number looks wrong.
• Exceptional attention to detail and a track record of owning recurring, deadline-driven work without dropped threads.
• Exposure to compensation fundamentals such as salary bands, job leveling, market benchmarking, or offer modeling, or clear evidence of the analytical aptitude and curiosity to pick them up quickly.
• Comfort handling highly confidential information with discretion and consistency.
• Clear, concise written communication , with the ability to explain a number or a process simply to someone who does not work in compensation.
• Interest in compensation and employment law (FLSA, pay transparency, pay equity), with a drive to build real expertise over time.
• High integrity and intellectual curiosity ; someone who asks why a process works the way it does instead of just running it.
• Background in Mathematics, Finance, Statistics, Economics, or a related quantitative field is preferred but not required.