Quantitative Operations Associate II- Lead Modeler

Responsibilities

• Develop and maintain volume forecasting, capacity planning, and resource optimization models
• Research and implement new predictive modeling and operations research methodologies
• Affordably support forecasting and capacity modeling consistency and innovation across team
• Routinely partner with Front Line Units (FLUs) to ensure model accuracy
• Conduct model production and performance presentations with executive leadership
• Serve as volume forecasting subject matter expert to help with analyst onboarding and training across Resource Analytics

Required Skills

• Master’s degree in Mathematics, Statistics, Applied Economics, Industrial Engineering, Operations Research, Advanced Analytics, other STEM field; or equivalent experience
• 5+ years of experience in quantitative roles modeling complex systems
• Fundamental understanding of linear regression, time series, and other predictive modeling techniques, both through education and professional experience
• Proficient in MS Office, particularly Excel and Copilot
• Proficient in SAS, Python, or R
• Ability to work in a team-oriented environment with strong aptitude for problem solving and collaboration
• Strong communication and interpersonal skills - specifically the ability to communicate complex ideas in a clear and concise manner to key stakeholders
• Natural curiosity and drive to answer important business questions
• High aptitude for self-motivation and self-determined project work in a fast-paced and rapidly changing environment
• Prior Banking industry analytics and modeling experience, specifically with developing models that adhere to standards set by a risk management governing body

Desired Skills

• Prior operational volume forecasting, capacity planning, or financial planning experience
• Experience with Arena or similar discrete event simulation software
• Experience with SAS OR, GAMS, XPRESS, CPLEX, or similar optimization software
• Tableau or other data visualization software experience
• Data mining experience using SQL/SAS querying
• Fundamental understanding of simulation and operations research techniques (discrete event simulation, Monte Carlo simulation, queuing theory, Markov chain modeling, optimization, etc.), both through education and professional experience

Benefits

The ideal candidate will have a keen eye for detail, a strong sense for modeling complex operational systems, excellent verbal and written communication skills, and the ability to coach junior analysts.

Pay

Commensurate with experience

Schedule

1st shift (United States of America)

Hours Per Week: 40