Quantitative Operations Associate II- Lead Modeler

Bank of AmericaChicago, IL
$126,000 - $168,700Onsite

About The Position

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! This job is responsible for developing and maintaining advanced models for the line of business, including volume forecasts, capacity plans, and vendor models. Key responsibilities include presenting findings to key stakeholders and ensuring compliance to Model Risk Management (MRM) standards. Job expectations include excellent quantitative skills and experience in time series forecasting, simulation modelling, operations research, and analytics. Resource Analytics team in Global Operations Data, Reporting & Operations Management is looking for a motivated individual with strong quantitative skills and experience in time series forecasting and predictive modeling. This individual will be responsible for developing and maintaining strategic volume forecasting and capacity planning models with the goal of maintaining optimal staffing levels across Global Operations. In addition, the position will involve quickly gaining subject matter expertise to 1) assist with analyst onboarding and training, and 2) ensure model adherence to Model Risk Management (MRM) requirements. 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.

Requirements

  • 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.

Nice To Haves

  • 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.

Responsibilities

  • Develop and maintain volume forecasting, capacity planning, and resource optimization models
  • Research and implement new predictive modeling and operations research methodologies
  • Assist in driving 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
  • Assist with documentation and other efforts to adhere to Model Risk Management (MRM) requirements
  • Serve as volume forecasting subject matter expert to help with analyst onboarding and training across Resource Analytics
  • Develops and maintains models for the line of business, including volume forecasts, capacity plans, and vendor models using advanced mathematical/statistical techniques
  • Drives horizontal consistency in model development, visualization, and usage across peer groups
  • Conducts routine model production and performance presentations with executive leadership
  • Ensures adherence to Model Risk Management (MRM) requirements
  • Supports ongoing model monitoring to improve forecasting performance and efficiency
  • Evaluates new opportunities and implement changes to improve model lifecycle processes
  • Demonstrates ability to operate independently, and ability train/mentor team members as needed

Benefits

  • Access to paid time off
  • Resources and support to our employees
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