Industrial Engineer – Operations Research

Role Overview

• Own and maintain decision-support algorithms and analytical models used across the distributed construction platform (e.g., inventory optimization, line balancing, labor planning, capacity planning, and logistics design)
• Execute and adapt decision-support models for new volumetric construction projects, ensuring consistency, accuracy, and relevance to project-specific assumptions
• Update, refine, and enhance optimization, simulation, heuristic, and meta-heuristic algorithms based on new data, business learnings, operational feedback, and changing constraints
• Partner closely with the Sr. Manager, Decision Support to translate strategic intent into executable, scalable analytical solutions
• Collaborate with technology and data engineering teams to support deployment, versioning, documentation, and maintainability of decision-support tools
• Prepare simulation models, scenarios, and what-if analyses to evaluate tradeoffs and support informed decision-making
• Reconcile model assumptions and outputs with actual operational performance; identify gaps and improvement opportunities
• Prepare clear, concise outputs (models, summaries, and visualizations) for internal stakeholders and leadership reviews
• Maintain and update documentation of algorithms, assumptions, inputs, and outputs to ensure accuracy, transparency and repeatability
• Conduct ad hoc analyses in support of innovation pilots, new concepts, and operational problem-solving

Requirements

• Master's degree in Industrial Engineering, Operations Research, Applied Mathematics or closely related field required
• 3-6 years or relevant experience applying quantitative models in operations, supply chain, logistics, or applied research environments required
• Proficiency in Python, including experience with Pandas, NumPy, optimization solver APIs (e.g. Gurobi), and data visualization libraries required
• Hands-on experience building and applying linear, integer, mixed‑integer, and nonlinear optimization models required
• Hands‑on experience with heuristics and/or meta‑heuristics (e.g., rule‑based heuristics, genetic algorithms, simulated annealing, tabu search, or related techniques) required
• Working knowledge of SQL and experience querying, validating, and reconciling structured datasets required
• Strong proficiency with Microsoft Excel and PowerPoint for modeling, analysis, and executive-ready communication required
• PhD coursework or research experience is a plus
• Experience using data visualization tools (e.g., Tableau, Power BI, Spotfire, Qlik) to communicate analytical insights effectively preferred
• Experience with discrete-event agent-based simulation frameworks is strongly preferred
• Experience applying AI assisted analytics—including predictive modeling, statistical analysis, and rule based or automated pattern detection techniques—to support data collection, data validation, prediction, and analytical workflow automation and optimization in decision support or operations contexts; machine learning experience is a plus
• Familiarity with Dash or building interactive analytical applications is a plus
• Familiarity with modern analytics and data science concepts, including model lifecycle management and continuous improvement is a plus

Tech Stack

• Numpy
• Pandas
• Python
• SQL
• Tableau

Benefits

• Generous time off including Paid Time Off, 13 annual holidays, and volunteer time off
• Day One Medical/Rx, Dental and Vision Plans
• Family friendly benefits including Paid Caregiver Leave, Paid Parental Leave and Adoption Reimbursement
• Performance/Incentive bonuses
• Career advancement, training opportunities, Employee Resource Groups, and tuition reimbursement
• Retirement programs including Matching 401(k) Contributions and Profit Sharing
• Employer paid Short-Term Disability, Long-Term Disability and Life Insurance
• myFlexPay partner – allows you to track, manage and access your pay anytime