Engineer, Industrial

Universal Orlando•Orlando, FL

About The Position

The Engineer, Industrial provides analytical decision support for Universal Destinations & Experiences leadership, influencing data-driven operational and workforce decisions. The role applies industrial engineering, operations research, and advanced analytics to improve efficiency, service delivery, and financial performance while supporting a high-quality guest experience. It uses quantitative methods for operational planning, capacity and demand analysis, and productivity improvement to design, implement, and sustain scalable decision-support solutions in a high-volume, guest-facing environment with variable demand and operational constraints. The position partners with operational leaders to define problems, frame decisions, and encourage adoption of data-driven solutions. It develops and maintains models for labor planning, workforce utilization, budgeting, scheduling, and hiring, balancing cost efficiency with service levels, guest experience, and operational needs. The role also acquires, prepares, and governs data; applies statistical and advanced analytics techniques; automates and scales analytics through cloud-based platforms; and creates dashboards, visualizations, business cases, and presentations for audiences from frontline operators to executive leadership. The role follows established Environmental, Health & Safety policies, procedures, and training, participates in related activities, and performs other duties as assigned.

Requirements

Bachelor’s degree in Industrial Engineering, Operations Research, Management Science, Decision Science, or a closely related field.
At least 3 years of applied industrial engineering and operational analysis experience, or equivalent experience.
Advanced proficiency in SQL and programming tools such as Python or R, including the ability to independently develop complex queries, analytical workflows, and reusable code.
Experience building reusable, production-ready analytics and decision-support solutions, including standardized metrics, governed datasets, automated analytical workflows, and sustained operating models.
Demonstrated experience applying optimization or operations research techniques in resource-constrained, variable-demand service environments.
Experience influencing operational decisions in complex, real-time or near-real-time environments while balancing efficiency, resource constraints, and guest or customer experience outcomes.
Experience with business intelligence and visualization platforms such as Power BI or Tableau, and cloud-based data platforms such as Snowflake or Azure.
Experience using modern analytics and productivity tools, such as Microsoft Copilot or ChatGPT, to improve analytical efficiency, code quality, and documentation.
Strong analytical judgment, conceptual thinking, and problem-solving abilities, including the ability to translate analysis into actionable recommendations.
Excellent interpersonal and consulting skills, including the ability to partner effectively with operations, finance, and technology stakeholders.
Experience conducting field studies and operational data collection to inform labor standards, productivity measurement, and capacity analysis.
Strong project management skills and ability to manage multiple initiatives simultaneously.
Commitment to knowledge sharing, best practices, and continuous improvement of analytical standards within the Business Analytics & Industrial Engineering team.
Willingness to support a 24/7/365 operation, including periods of high demand such as weekends and holidays.

Nice To Haves

Master’s degree in Industrial Engineering, Operations Research, Management Science, Decision Science, or a closely related field.
At least 2 years of experience performing operational analyses for theme parks, resorts, retail, dining, entertainment venues, or similar environments.

Responsibilities

Design, operationalize, and sustain end-to-end analytical and decision-support solutions using industrial engineering and business analytics principles.
Apply probability and statistics, process flow analysis, queuing theory, mathematical optimization, scenario modeling, and prescriptive optimization to diagnose problems, evaluate trade-offs, and recommend actionable solutions.
Develop and maintain decision-support models for labor planning, workforce utilization, budgeting, scheduling, and hiring strategies, balancing cost efficiency, service levels, guest experience, and operational realities.
Partner with operational leaders to define problems, frame decisions, and drive adoption of data-driven solutions.
Improve analytical solutions using advanced analytics techniques, modern programming practices, and analytics and productivity tools.
Acquire and prepare data using database querying tools and modern data pipelines.
Consolidate, clean, standardize, and maintain analysis-ready datasets from multiple enterprise systems as governed sources of truth.
Apply forecasting, classification, anomaly detection, trend analysis, and other statistical techniques to understand performance drivers and validate insights.
Identify and implement opportunities to automate and scale analytics by productionizing metrics, models, and decision logic in cloud-based platforms for real-time and scenario-based decision-making.
Develop business cases and presentations for audiences ranging from frontline operators to senior and executive leadership.
Create dashboards, visualizations, and standardized performance and decision-support systems that help stakeholders assess scenarios, understand trade-offs, and act.
Translate complex analytical findings into concise narratives that drive alignment and action.
Follow established Environmental, Health & Safety policies, procedures, and training, and participate in related team member activities.
Perform other duties as assigned.