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Tysons, VA, United States · Mc Lean, VA, United States, 22102
Overview
About M.C. Dean
M.C. Dean is Building Intelligence. We design, build, operate, and maintain cyber-physical solutions for the nation’s most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 7,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration.
Why Join Us?
Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values—agility, expertise, and trust—we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries.
Responsibilities
M.C. Dean is seeking a Senior Compensation Analyst to lead advanced compensation analytics and modeling efforts across a diverse workforce spanning engineering, construction, manufacturing, and technology. This role is critical in building scalable, data-driven compensation programs that support a high-performance culture and evolving workforce strategy.
This position requires deep expertise in Excel-based modeling, emerging AI-enabled analytics, and multi-industry compensation benchmarking to inform strategic pay decisions at all levels of the organization.
Develop and maintain complex Excel-based compensation models, including:
Merit and promotion modeling
Scenario analysis for compensation strategy decisions
Leverage AI tools and advanced analytics to:
Identify compensation trends and anomalies
Automate aspects of benchmarking, pay analysis, and reporting
Build dashboards and tools to support real-time compensation insights for leadership
Conduct compensation benchmarking across multiple labor markets, including:
Engineering
Technology and corporate functions
Utilize survey data (e.g., Mercer, Radford, industry-specific sources) and alternative data inputs
Qualifications
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