Federal Pricing and Win Strategy Lead

Introduction

Expert Price-to-Win (PTW) lead with deep expertise in federal acquisition, competitive intelligence, pricing strategy, financial modeling, and AI-enabled analytics. Serves as a trusted advisor to capture, proposal, and executive leadership teams by developing data-driven pricing strategies that maximize win probability while achieving profitability objectives. Leverages advanced cost estimating, market research, predictive modeling, machine learning, and generative AI tools to analyze procurement trends, assess competitor behavior, forecast winning price ranges, and support strategic bid decisions.

Combines strong business acumen, quantitative analysis, and federal contracting knowledge to drive growth, improve win rates, and optimize contract performance across the federal marketplace.

As a Pricing and Technical SME you will be responsible for the implementation and management of our "Price to Win (PTW)" capability and work with a team of SMEs. This position must have extensive experience performing PTW Price to Win & Technical analysis and provide high quality PTW targets and recommendations for highly competitive Federal procurements. The quantitative Data analyst must be a self-starter that has the exceptional ability to analyze solicitation requirements, evaluation factors, customer spend data, customer budgets, award trends, competitive landscape, competitor bid tendencies and competitor bid capabilities in deriving accurate PTW targets and recommendations.

This person must have excellent communication, technical and presentation skills, with the ability to support executive reviews and present PTW targets and recommendations to Senior leadership in a convincing manner. Additionally, the data expert must be a team player that is able to effectively collaborate with other functional leads.

• Collect and analyze large data sets to determine trends, and provide reports in visual forms such as graphs, charts and dashboards.

Master's Degree

• Expert knowledge of FAR and agency supplements (DFARS, GSAM, HSAR, VAAR, etc.)
• Understanding of federal procurement processes, source selection methods, and evaluation criteria
• Knowledge of contract types (FFP, CPFF, CPAF, T&M, IDIQ, BPA)
• Experience with cost realism, price reasonableness, and best-value tradeoff evaluations
• Understanding of federal budgeting, appropriations, and acquisition planning

• Development and execution of Price-to-Win methodologies
• Competitive assessment and market intelligence analysis
• Win probability and affordability analysis
• Competitor pricing and incumbent positioning analysis
• Pricing strategy development aligned with capture and proposal objectives
• Margin optimization and strategic tradeoff analysis

• Basis of Estimate (BOE) development
• Bottom-up, parametric, and historical cost estimating
• Labor rate, indirect rate, escalation, and wrap-rate modeling
• Profitability, ROI, NPV, and cash-flow analysis
• Scenario planning, sensitivity analysis, and financial risk assessment
• Cost volume development and pricing compliance reviews

• Statistical analysis and predictive modeling
• Regression analysis and trend forecasting
  
  Monte Carlo simulations and probabilistic modeling
• Data mining, benchmarking, and market analysis
• Quantitative decision support and risk modeling
• Development of data-driven pricing recommendations

• Expert proficiency in Microsoft Excel
  • Financial modeling
  • Pivot Tables
  • Power Query/Power Pivot
  • VBA and automation
  • Dashboard development
• SQL and database querying
• Data visualization and reporting

• Microsoft Power BI
• Tableau
• Federal procurement databases and market intelligence tools
• SAM.gov, FPDS-NG, USA spending.gov, agency forecasts, and contract award repositories

• Statistical analysis and predictive modeling
• Regression analysis and trend forecasting
• Monte Carlo simulations and probabilistic modeling
• Data mining, benchmarking, and market analysis
• AI-assisted competitive intelligence and market research
• Machine learning applications for price prediction and win probability analysis
• Predictive analytics using historical procurement and award data
• Large Language Model (LLM) applications for acquisition research, solicitation analysis, and proposal support
• Generative AI tools for data synthesis, trend identification, and scenario development
• Development of AI-enhanced pricing models and decision-support tools
• Quantitative risk analysis and optimization modeling
• Data visualization and executive decision analytics