Quantitative Operations Associate

• Develop and maintain models for the line of business, including volume forecasts, capacity plans, and vendor models
• Drive horizontal consistency in model development and usage across peer groups
• Conduct routine model production and performance presentations with executive leadership
• Ensure adherence to Model Risk Management (MRM) requirements
• Support ongoing model monitoring to improve forecasting performance and efficiency
• Develop and implement models for volume forecasting, capacity planning, workforce scheduling, scenario analysis, and operational performance reporting
• Apply advanced analytical methods to real-world business challenges
• Translate analytical findings into practical, data-driven recommendations

• Master’s degree in industrial engineering, operations research, or a related STEM field
• Proficiency with Microsoft Excel, PowerPoint, and VBA
• Experience querying databases using SQL
• Experience developing and implementing discrete-event simulation and optimization models
• Experience using Git Hub Copilot to accelerate model development and formulate heuristics
• Strong problem-solving and collaboration skills
• Demonstrated ability to apply quantitative methods to business problems
• Ability to work effectively through ambiguity, complexity, and change
• Excellent written and verbal communication skills
• Experience in capacity planning, financial planning, or quantitative modeling
• Proficiency with Arena or comparable discrete-event simulation software
• Proficiency with Gurobi or comparable optimization software
• Experience with Python, SAS, SQL, and data mining
• Banking analytics and modeling experience, particularly in volume forecasting and capacity or resource optimization
• Experience developing models under model risk management standards and governance requirements
• Knowledge of linear regression, time-series analysis, and other statistical modeling techniques

Demonstrates expertise in developing and maintaining advanced models for volume forecasting, capacity planning, and operational performance reporting, while ensuring compliance with Model Risk Management standards. Proficient in applying quantitative methods and advanced analytical techniques to drive data-driven business recommendations.

• Master’s Degree In Industrial Engineering
• Proficiency With Microsoft Excel
• Experience With SQL
• Proficiency With Arena Or Comparable Discrete-Event Simulation Software
• Experience Developing Models Under Model Risk Management Standards

• Volume Forecasting
• Capacity Planning
• Discrete-Event Simulation
• Optimization Models
• Quantitative Modeling
• Statistical Modeling Techniques
• Data Mining
• Linear Regression
• Time-Series Analysis
• Heuristics Formulation

• Problem-Solving
• Collaboration
• Communication

• Model Risk Management
• Banking Analytics
• Operational Performance Reporting
• Scenario Analysis
• Workforce Scheduling

• VBA
• Git Hub Copilot
• Gurobi
• Python
• SAS