Cost and Schedule Analysis Engineer

Peraton•Annapolis Junction, MD

About The Position

Peraton Labs is seeking a quantitative engineer to build the analytical engines that power cost and schedule analysis capabilities within an advanced program management platform. This role translates earned value management principles, schedule analysis methodologies, and financial forecasting techniques into automated, scalable software components that deliver actionable insights to program managers and oversight personnel.

Requirements

Minimum of 5+ years of experience with a Bachelor's degree, 3+ years with a Master's degree, or a PhD in Engineering, Finance, Mathematics, Statistics, Computer Science, or related field
Direct software engineering experience with a focus on quantitative analysis or financial modeling
Strong Python proficiency; experience with numerical computing libraries (NumPy, pandas, SciPy)
Understanding of earned value management principles and metrics
Experience with schedule analysis concepts (critical path method, float, schedule compression)
Familiarity with statistical forecasting and time series analysis
Experience with data validation and quality assurance for analytical systems
Strong mathematical and analytical reasoning skills
US Citizenship with the ability to obtain/maintain a Secret clearance

Nice To Haves

Direct experience with EVM systems or defense cost reporting
Experience with Monte Carlo simulation (Crystal Ball, @Risk, or custom implementations)
Familiarity with IMS data formats (Microsoft Project XML, Primavera XER/XML)
Knowledge of IPMDAR/IPMR data elements and reporting requirements
Experience with financial modeling or cost estimation

Responsibilities

Develop EVM analytics engines: CPI, SPI, TCPI, EAC, VAC, and IEAC calculations with trend analysis and forecasting
Build IMS parsing and analysis capabilities: critical path identification, float analysis, schedule health metrics, and baseline comparison
Implement budget vs. actuals variance analysis with drill-down by WBS element, control account, and organizational structure
Develop forecasting models that incorporate both quantitative EVM trends and qualitative signals from unstructured analysis
Build schedule risk analysis (SRA) capabilities including Monte Carlo simulation integration
Implement data validation and anomaly detection for cost and schedule data inputs
Create reusable analytical components that can be invoked through the platform's automation framework
Collaborate with PM Domain Analysts to validate analytical accuracy against established standards