Quantitative Operations Associate – Volume Forecaster

• Develop and maintain models for the line of business, including volume forecasts, capacity plans, and vendor models
• Develop and maintain time-series models using advanced algorithm-based forecasting techniques
• Partner routinely with Front-Line Units to ensure model accuracy
• Present model production and performance findings to executive leadership and key stakeholders
• Support ongoing model monitoring to adhere to Model Risk Management guidelines
• Drive forecast consistency and innovation across the team
• Drive horizontal consistency in model development and usage across peer groups
• Improve forecasting performance and efficiency
• Apply statistical models and business intelligence to maintain strategic volume forecasts for capacity planning

• Master's degree in Mathematics, Statistics, Applied Economics, Analytics, Data Science, or another STEM field; or equivalent experience
• 2+ years of experience in quantitative roles supporting complex functions
• Fundamental understanding and experience with linear regression, time-series, and other statistical modeling techniques
• Proficient in MS Office, particularly Excel and Copilot
• Experience with SAS, Python, or R
• Ability to work in a team-oriented environment with strong problem-solving and collaboration aptitude
• Strong communication and interpersonal skills, including communicating complex ideas clearly and concisely to key stakeholders
• Natural curiosity and drive to answer important business questions
• 2+ years of experience as a professional predictive modeling analyst (desired)
• Prior banking industry analytics and modeling experience with risk-management standards (desired)
• Data mining experience using SQL (desired)
• Experience with Tableau or other data visualization (desired)
• Ability to coach others (desired)

Demonstrates expertise in developing and maintaining statistical models for forecasting and capacity planning, with a strong foundation in linear regression and time-series analysis. Proficient in utilizing advanced analytics tools and techniques to drive model accuracy and performance in a collaborative environment.

• Statistical Modeling Techniques
• Predictive Modeling Analysis
• Data Visualization with Tableau
• Experience with SAS, Python, or R
• Master's Degree in Mathematics, Statistics, or Related Field

• Linear Regression
• Time-Series Analysis
• Statistical Modeling
• Data Mining with SQL
• Forecasting Techniques

• Strong Communication Skills
• Problem-Solving Aptitude
• Collaboration Skills
• Natural Curiosity

• Model Risk Management
• Banking Industry Analytics
• Capacity Planning
• Vendor Models

• MS Office
• Excel
• Copilot
• SAS
• Python
• R
• Tableau