Senior Compensation Analyst

Human Resources Opportunity in Financial Services

Senior Compensation Analyst

Location(s):

Atlanta: 2300 Windy Ridge Pkwy SE, Suite750, Atlanta, GA 30339

La Vista:12325 Port Grace Blvd, La Vista, NE 68128

Oakdale: 7755 3rd St. N, Oakdale, MN 55128

Scottsdale: 18700 N Hayden Rd, Suite 255, Scottsdale, AZ 85255

St. Petersburg: 877 Executive Center Dr. W, Suite 300, St. Petersburg, FL 33702

Osaic is not considering remote candidates at this time.

Osaic has returned to the office on a hybrid schedule requiring a minimum of 4 days weekly in the office. Applicants should be located at one of our hubs listed above and must be willing to work this schedule.

Role Type:

Full-time, Exempt

Salary: $100,000 - $125,000 per year + annual performance-based bonus

Actual compensation offered will be determined individually, based on several job-related factors, including location, skills, licensure, experience, and education.

Our competitive compensation is just one component of Osaic's total compensation package. Additional benefits include health, vision, dental insurance, 401k, paid time away, volunteer days and much more. To view more details of what you can look forward to, visit our careers page:Osaic Benefits.

Summary:

The Senior Compensation Analyst is a highly influential individual contributor responsible for advancing the organization's compensation capabilities, analytics, and infrastructure. This role will play a critical part in stabilizing and modernizing compensation practices, with an immediate focus on data integrity, job architecture refinement, and scalable analytics.

Operating in a fast-evolving environment, this role will partner closely with the VP of Total Rewards and Compensation Manager to build foundational and advanced capabilities across compensation programs. The ideal candidate brings strong technical expertise in Workday, advanced Excel modeling, and data visualization, along with a builder mindset and the ability to operate effectively in ambiguity. This role will also help shape the organization's early-stage approach to AI-enabled compensation analytics and reporting.

Education Requirements:

Bachelor's degree in Human Resources, Business, Finance or a related field preferred, high school diploma (or equivalent) in combination with significant practical experience will be considered in lieu of degree.Minimumofhighschool diploma or equivalent isrequired.

Responsibilities:

Compensation Program Execution & Advisory

• Support the design, execution, and continuous improvement of compensation programs, including base pay, incentives, and recognition
• Serve as a trusted advisor to HR Business Partners and business leaders on offers, promotions, market adjustments, and pay decisions
• Provide practical, data-informed recommendations in a fast-moving, evolving environment

Job Architecture & Benchmarking

• Partner in the validation, refinement, and ongoing management of job architecture based on the McLagan framework
• Review and update job descriptions, job profiles, leveling, and job family assignments
• Conduct job evaluations, including FLSA classification and leveling alignment
• Benchmark roles using survey data and market intelligence to ensure external competitiveness

Data Cleanup, Integrity & Infrastructure

• Lead efforts to assess, clean, and standardize compensation and job data within Workday
• Identify data gaps, inconsistencies, and risks, and implement practical solutions to improve data quality
• Establish repeatable processes and governance for maintaining high-quality compensation data
• Partner with HRIS to improve system structure, data flows, and usability

Advanced Analytics & Reporting Transformation

• Build and enhance compensation reporting using advanced Excel and Workday reporting capabilities
• Develop scalable dashboards and visualizations (e.g., Power BI) to support decision-making
• Transition reporting from manual and reactive to automated and insight-driven
• Deliver actionable insights on trends such as pay equity, compression, retention risk, and market positioning

Annual Compensation Processes

• Lead execution of the annual merit and bonus planning cycles
• Build models, tools, and reporting to support effective planning and budget alignment
• Partner with Finance and HR to ensure alignment between compensation decisions and financial targets

Incentive Plan Support

• Support design, modeling, and administration of incentive plans, including collaboration with Finance and Sales leadership
• Assist in documentation and communication of plan designs

Innovation, Automation & AI Enablement

• Identify opportunities to streamline and automate compensation processes using analytics, tools, and emerging technologies
• Begin introducing and shaping the use of AI in compensation analytics, reporting, and process efficiency
• Partner with leadership to explore practical, scalable applications of AI in Total Rewards
• Drive a mindset of continuous improvement and modernization

Documentation & Enablement

• Create clear, structured documentation for compensation programs, processes, and tools
• Support training and enablement of HR partners and leaders

Basic Requirements:

• Bachelor's degree in Human Resources, Finance, Data Analytics, or related field
• 7+ years of progressive compensation experience
• Strong experience with job architecture, job leveling, and benchmarking
• Demonstrated experience with annual merit and bonus cycles
• Advanced proficiency in Excel (complex modeling, data manipulation, scenario analysis)
• Hands-on experience with Workday Compensation and reporting (beyond standard report running)
• Ability to work effectively in ambiguous, evolving environments
• Strong analytical, problem-solving, and stakeholder communication skills

Preferred Qualifications:

• Experience with Power BI or other data visualization tools
• Exposure to data cleanup, transformation, or system optimization efforts
• Early experience with or strong interest in AI tools and applications in HR/Compensation
• CCP certification
• Experience working within a McLagan framework or similar job architecture models