["Sr. Compensation Analyst - Tysons, VA","Sr. Compensation Analyst - Tysons, VA"]

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.

Compensation Strategy & Program Design

• Design and enhance compensation programs including base pay structures, incentive plans, and pay-for-performance frameworks

• Support compensation strategies aligned with M.C. Dean's evolving workforce model, including manufacturing and technical career pathways

• Partner with HR and business leaders to ensure compensation programs drive retention, performance, and internal equity

Advanced Modeling & Analytics (Excel + AI)

• Develop and maintain complex Excel-based compensation models , including:

• Merit and promotion modeling

• Workforce cost forecasting

• Scenario analysis for compensation strategy decisions

• Leverage AI tools and advanced analytics to:

• Identify compensation trends and anomalies

• Improve forecasting accuracy and decision-making speed

• Automate aspects of benchmarking, pay analysis, and reporting

• Build dashboards and tools to support real-time compensation insights for leadership

Market Benchmarking Across Industries

• Conduct compensation benchmarking across multiple labor markets , including:

• Engineering

• Construction trades and field operations

• Manufacturing and production roles

• Technology and corporate functions

• Utilize survey data (e.g., Mercer, Radford, industry-specific sources) and alternative data inputs

• Translate market data into actionable salary structures, ranges, and pay recommendations

• Provide guidance on geographic differentials and competitive positioning

Performance & Pay Integration

• Lead analytics for annual compensation cycles, including merit increases, promotions, and incentive payouts

• Evaluate pay-for-performance alignment using data-driven insights

• Support executive-level compensation decision-making with robust modeling and scenario analysis

Data Analysis, Reporting & Executive Insights

• Produce clear, data-driven insights and presentations for senior leadership

• Conduct pay equity and compression analyses , identifying risks and recommending solutions

• Prepare compensation recommendations and materials for executive approval processes

Job Architecture & Workforce Planning

• Support development and maintenance of job architecture, leveling frameworks, and career paths

• Align compensation structures with workforce planning and succession strategies

• Contribute to organizational design initiatives through compensation insights

Compliance & Governance

• Ensure compliance with all applicable compensation regulations

• Support audits and maintain documentation of compensation decisions and methodologies

• Ensure integrity and accuracy of compensation data and models

Qualifications

• Bachelor's degree in Human Resources, Finance, Economics, Data Analytics, or related field

• 5+ years of progressive compensation experience

• Advanced proficiency in Excel (modeling, scenario analysis, large datasets)

• Experience using AI tools or advanced analytics for workforce or compensation insights

• Demonstrated experience conducting multi-industry compensation benchmarking

• Strong analytical, problem-solving, and data visualization skills

Preferred

• Experience in engineering, construction, manufacturing, or technology sectors

• Familiarity with compensation tools and survey platforms (Mercer, Radford, etc.)

• Experience supporting director- and executive-level compensation decisions

• CCP (Certified Compensation Professional) or equivalent

• Experience building scalable analytics tools or dashboards (Power BI, Tableau, etc.)

Key Competencies

• Advanced analytical and modeling capability

• Strategic thinking with strong business acumen

• Ability to synthesize complex data into clear recommendations

• Strong stakeholder management and communication skills

• High level of discretion and attention to detail

Abilities:

• Exposure to computer screens for an extended period of time.

• Sitting for extended periods of time.

• Reach by extending hands or arms in any direction.

• Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard.

• Listen to and understand information and ideas presented through spoken words and sentences.

• Communicate information and ideas in speaking so others will understand.

• Read and understand information and ideas presented in writing.

• Apply general rules to specific problems to produce answers that make sense.

• Identify and understand the speech of another person.