Total Rewards Analyst: AI-Driven Pay & Benefits

Rozgoo; United States; A distancia; USD 80.000 - 110.000; Jornada completa

Descripción de la vacante

Drata is seeking a Total Rewards Analyst to improve compensation programs, support benefits and total rewards operations, and drive scalable insights. The role emphasizes turning market and employee data into actionable recommendations, guiding merit, bonus, and equity cycles, and implementing approved AI tools to speed analysis with human oversight.

Confidentiality is essential. The candidate will partner with HRIS, People Ops, Finance, and vendors, ensuring accurate data across systems and

Formación

• 2–4 years of experience in compensation, total rewards, benefits, HR analytics, HRIS, or a closely related field.
• Experience analyzing compensation data, interpreting market benchmarks, and building recommendations from quantitative information.
• Strong Excel or Google Sheets skills, including pivot tables, lookups, data validation, and financial or compensation modeling.

Responsabilidades

• Analyze internal compensation data and external market data to support salary ranges, job leveling, compa‑ratio analysis, pay equity reviews, and compensation recommendations.
• Support the planning and execution of annual merit, bonus, and equity review processes, including modeling, budgeting, manager guidance, system preparation, testing, communications, and post‑cycle audits.
• Prepare analyses and recommendations for new hires, promotions, transfers, off‑cycle adjustments, and other pay actions.
• Support the administration and continuous improvement of base pay, incentive, equity, and recognition programs.
• Maintain accurate job, level, range, and compensation data across relevant systems and documentation.
• Validate compensation changes and equity inputs for accuracy, consistency, policy alignment, and internal equity.
• Provide operational support for health and welfare, retirement, leave, wellness, and other benefits programs.
• Partner with benefits vendors and internal stakeholders to investigate employee questions, resolve data discrepancies, and monitor service delivery.
• Support benefits eligibility, enrollment, invoice, utilization, and renewal analyses as needed.
• Identify opportunities to automate recurring workflows, such as data validation, reconciliation, reporting, survey preparation, communications, and intake triage.
• Use approved AI tools to accelerate analysis, generate first drafts, summarize trends, and improve self‑service—while applying human review to all outputs and decisions.
• Build or improve lightweight automations, templates, prompts, and operating procedures that reduce manual effort and improve accuracy.
• Partner with HRIS, People Operations, Finance, and appropriate technical partners to improve integrations, reporting, controls, and workflow design.
• Support compliance with applicable compensation, pay transparency, pay equity, benefits, and record‑keeping requirements.
• Perform regular audits and reconciliations across HRIS, compensation, equity, payroll, benefits, and reporting data.
• Escalate data issues, policy exceptions, and potential compliance risks promptly and thoughtfully.
• Handle sensitive questions with discretion, empathy, and sound judgment.
• Manage multiple priorities in a fast‑moving environment while meeting deadlines and maintaining a high bar for accuracy.

Conocimientos

Excel/Sheets

Pivot tables

Lookups

Data validation

Financial modeling

Educación

Bachelor’s degree in HR/Business/Finance/Economics/Statistics

Herramientas

Workday

Descripción del empleo

Drata is seeking a Total Rewards Analyst to improve compensation programs, support benefits and total rewards operations, and drive scalable insights. The role emphasizes turning market and employee data into actionable recommendations, guiding merit, bonus, and equity cycles, and implementing approved AI tools to speed analysis with human oversight.

Confidentiality is essential. The candidate will partner with HRIS, People Ops, Finance, and vendors, ensuring accurate data across systems and