Total Rewards Analyst: Compensation & Data Insights

NFP Corp; Indianapolis (IN); Hybrid; USD 65,000 - 80,000; Full time

Benefits offered by this job

PTO & paid holidays

401(k) with match

Health & wellness programs

Exclusive discount programs

Job summary

NFP Corp seeks a Total Rewards Analyst to provide technical support for compensation and total rewards engagements. You will create analyses, reports, and communications for external clients, working independently and in teams. Hybrid role in CST or EST time zones is preferred.

Responsibilities include benchmarking roles, preparing observations, developing pay structures, and supporting client projects with data-driven recommendations. Strong Excel skills and analytical abilities are essential.

Qualifications

• Bachelor's degree in finance, human resources, business, or related field.
• Minimum of one year of experience in compensation, data analysis, benefits, human resources, or related field.
• Desire to obtain CCP, SHRM-CP or other related certification preferred.
• Experience in a consulting environment preferred.

Responsibilities

• Benchmark and evaluate client roles and plan design aspects for market competitiveness.
• Prepare compensation observations, analyses, and recommendations.
• Assist with client project management.
• Create client communications and deliverables to support the practice.
• Develop pay structures using benchmark data and client objectives as a guide.
• Complete employee analysis reports, comparing employees to new pay structures.
• Participate in client review meetings to gather and document feedback.

Skills

Analytical

Excel

Education

Bachelor's degree in finance, HR, business, or related field

Job description

NFP Corp seeks a Total Rewards Analyst to provide technical support for compensation and total rewards engagements. You will create analyses, reports, and communications for external clients, working independently and in teams. Hybrid role in CST or EST time zones is preferred.

Responsibilities include benchmarking roles, preparing observations, developing pay structures, and supporting client projects with data-driven recommendations. Strong Excel skills and analytical abilities are essential.