Compensation Analyst

The Sage Group; United States; On-site; USD 90,000 - 140,000; Full time

Job summary

The Sage Group is seeking a hands-on Compensation / People Data Analyst contractor to drive day-to-day analytics, data gathering, and modeling for the Compensation team. You will partner with senior Compensation Business Partners to deliver actionable insights for HRBPs, Talent Acquisition, and leadership.

Ideal candidates are independent, adept at managing priorities, and can structure complex compensation questions into clear recommendations, with strong benchmarking experience and tooling.

Qualifications

• 3–5+ years in Compensation/Total Rewards or HR analytics.
• Experience with compensation planning cycles and core programs.
• Hands-on benchmarking using Radford, Mercer, or WTW.
• Advanced analytical and modeling skills; interpret data to recommendations.
• Proficient in Google Sheets/Excel, Databricks, and SQL.
• Experience building reusable data models and automated analytics.
• Knowledge of internal ranges, market pricing, and survey methods.

Responsibilities

• Model compensation scenarios to quantify cost, impact, and tradeoffs.
• Build dashboards and data models from large data sets.
• Develop materials for Compensation Business Partners and HRBPs.
• Support deep-dive analyses (retention, top-talent, comp correlations).
• Provide analytics during and after compensation cycles.
• Use market survey data (Radford, Mercer, WTW) with internal ranges to guide decisions.
• Prepare analytics and tools to support offer reviews for L60 and below.
• Build models for merit, bonus, equity refresh, and mid-cycle reviews.
• Contribute to pay analyses, tooling, and program execution.

Skills

Analytical skills

Data modeling

Data interpretation

Communication of insights

Stakeholder collaboration

Tools

Google Sheets/Excel

Databricks

SQL

Radford

Mercer

WTW

Job description

We are seeking a hands-on Compensation / People Data Analyst contractor to support the Compensation team with day-to-day analytics, data gathering, modeling, tooling, and program execution. This role will partner closely with senior Compensation Business Partners to deliver clear, actionable insights for HRBPs, Talent Acquisition, and business leadership.

The ideal candidate is comfortable working independently, managing competing priorities, and bringing structured thinking to complex compensation questions. Strong compensation modeling, data tooling, and market benchmarking experience are required.

Responsibilities

• Model compensation scenarios and program inputs to quantify cost, impact, and tradeoffs.
• Work with large data sets to build reusable analytics, dashboards, and data models that automate insights and findings.
• Develop materials and analyses that Compensation Business Partners can use with HRBPs, Talent Acquisition, and leadership teams.
• Support deep-dive analyses, including retention investment, top-talent and compensation correlation, quarterly business review data, and performance rating analysis.
• Provide compensation analytics during and after compensation planning cycles.
• Use market survey data from Radford, Mercer, and WTW, along with internal salary ranges, to support compensation decisions.
• Prepare analytics and tools to support offer recommendation reviews for L60 and below roles, including new hires and internal mobility.
• Build and maintain models supporting core compensation programs, including merit, bonus and commission cycles, equity refresh, and mid-cycle reviews.
• Contribute to pay analyses, compensation tooling, and broader program execution.

Qualifications

• 3–5+ years of experience in Compensation, Total Rewards, People Analytics, HR Analytics, or a related function.
• Experience supporting compensation planning cycles and core compensation programs.
• Hands-on experience with compensation benchmarking and market survey tools, including Radford, Mercer, and/or WTW.
• Advanced analytical and modeling skills, with the ability to interpret data and communicate clear recommendations.
• Strong working knowledge of Google Sheets and/or Excel, Databricks, and SQL.
• Experience building reusable data models, reporting tools, and automated compensation analytics.
• Knowledge of internal compensation ranges, market pricing, and compensation survey methodology.