Customer and Project Analysis Manager

About the role

The Customer and Project Analysis Manager leads the development of customer, project, and profitability analytics models to inform pricing strategy, customer segmentation, and margin improvement. This is a hands-on, working manager role responsible for building scalable analytics, leading complex data modeling, and converting insights into actionable recommendations. The role partners closely with Sales, Operations, and Finance to influence decisions at all levels from field leadership to senior executives.

Responsibilities

• Leads comprehensive customer profitability analysis, incorporating margin, price realization, credit risk, DSO, and cost-to-serve metrics.

• Develops and maintains customer stack rankings to inform pricing strategy, account prioritization, and resource allocation.

• Builds customer profiles and segmentation models (e.g., pricing tiers, behavioral segments, risk categories) to support more sophisticated and differentiated pricing strategies.

• Develops repeatable, scalable project profitability models that quantify full cost-to-serve and margin drivers.

• Translates complex analytics into clear, actionable recommendations for Sales, Operations, and National Accounts.

• Identifies and quantifies key pricing and project levers (e.g., utilization, scope creep, service intensity, and contract structure).

• Works side-by-side with Finance (FP&A) to align analytical outputs with financial reporting, forecasts, and margin targets.

• Conducts customer and job site visits to validate analytics, understand real-world drivers, and build business acumen.

• Builds and maintains scalable dashboards, data models, and reporting frameworks that enable ongoing performance tracking.

Requirements

• Bachelor’s degree in Finance, Business, Economics, or related field.
• 5+ years of experience in financial analysis, customer analytics, project economics, or commercial strategy.
• Demonstrated experience building customer profitability and cost-to-serve models.
• Strong data modeling and analytical skills, including experience with large datasets and structured analysis.
• Proficiency with analytics tools (Excel required; SQL, BI tools, or similar) preferred.
• Ability to translate complex data into clear, actionable insights for business stakeholders.