Project Controls Engineer III — Risk Management Pro

Averro; Rockville (MD); On-site; USD 90,000 - 130,000; Full time

Job summary

Averro is seeking a Project Controls Engineer III (Risk Management) to provide risk-focused project controls across the full lifecycle, interfacing with cost, schedule, estimating, and change management teams. The role emphasizes guiding risk owners, performing quantitative analyses, and communicating conclusions to internal stakeholders and the DOE.

Ideal candidates will have strong ARM, Monte Carlo, and scheduling experience, with a background in engineering and a track record of integrating

Qualifications

• Bachelor's degree in Engineering required.
• 5+ years of experience in a risk management function within project controls.
• Experience building risk registers and supporting a risk manager.
• Proficiency in quantitative risk analysis tools (Crystal Ball, @Risk).
• Experience with scheduling (Primavera P6) and ARM or similar risk register software.
• Proficiency in Microsoft Excel.

Responsibilities

• Guide risk owners and PCEs through the full risk lifecycle: identification, documentation, quantification, review, and closure.
• Lead quantitative risk analyses (Monte Carlo, SRA, CRA) for DOE reporting and internal use.
• Maintain risk registers in ARM or equivalent software and integrate risk with cost and schedule data.
• Produce risk-based forecasts and risk dashboards for management and customers.
• Coordinate with change management and scheduling teams to connect risk outputs to schedules.

Skills

Risk management

Quantitative risk analysis

Excel

Stakeholder communication

Project controls

Education

Bachelor's degree in Engineering

Tools

Crystal Ball

@Risk

Active Risk Manager (ARM)

P6 (Primavera)

Job description

Averro is seeking a Project Controls Engineer III (Risk Management) to provide risk-focused project controls across the full lifecycle, interfacing with cost, schedule, estimating, and change management teams. The role emphasizes guiding risk owners, performing quantitative analyses, and communicating conclusions to internal stakeholders and the DOE.

Ideal candidates will have strong ARM, Monte Carlo, and scheduling experience, with a background in engineering and a track record of integrating