Description
About Alvarez & Marsal
Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients' problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work—guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity - are why our people love working at A&M.
The Team
We are seeking a detail-oriented and analytically-minded Compensation Associate to join our Global People Organization. In this role, you will develop and maintain job architecture, conduct market benchmarking, and support compensation analytics across multiple regions - some starting from scratch, others building on existing frameworks. You'll partner with HR leadership to analyze external market data, identify compensation trends, and support annual pay equity reviews. This is a foundational analytical role with direct impact on how we price roles across a 12,000+ person global organization. This role requires 2–3 days per week onsite, with flexibility to increase office presence based on business needs
How you will contribute
- Develop and maintain job architecture (levels, grades, compensation bands) for assigned locations, building from existing frameworks or initiating new structures as needed.
- Conduct annual market benchmarking using Mercer and Aon databases for assigned roles; analyze external market data and prepare positioning recommendations.
- Assist with compilation, validation, and submission of compensation data to market survey vendors (e.g., Mercer, Aon) for annual survey cycles, ensuring accuracy and on-time delivery.
- Support targeted market analyses as needed between annual cycles in response to business requests.
- Create reports and dashboards to track compensation data; identify data quality issues and recommend standardization.
- Support annual pay equity audit process - identify and flag potential gaps by gender, race, and tenure; prepare data summaries and findings for leadership review.
- Manage compensation data with confidentiality and accuracy; flag trends and recommend operational improvements.
Qualifications
- Bachelor's degree in HR, Business, Economics, Finance, or related field.
- 2-3 years of compensation, HR analytics, or related experience
- Knowledge of compensation principles and practices; familiarity with multi-region or global compensation a plus.
- Advanced Excel skills (pivot tables, VLOOKUP, data analysis); strong attention to detail and ability to work with large datasets.
- Ability to translate data and analysis into clear written recommendations.
- Hands-on experience with compensation benchmarking databases (Mercer, Aon, or similar) is strongly preferred.
- Experience with job architecture, job leveling, or compensation banding strongly preferred.
- Highly organized and able to manage multiple priorities in a dynamic setting.
- Strong communication and analytical skills; effective independent contributor.
- Proficiency with Microsoft Excel, Word, and PowerPoint.
Your journey at A&M
We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person’s unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career. We prioritize your well-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M. The possibilities are endless for high-performing and passionate professionals.
