Global Operations Modelling Lead

Job Description:

Global Operations (GO) Resource Analytics team is looking for a motivated individual with strong quantitative skills and experience in time series forecasting, simulation modelling, operations research, and analytics. This individual will be responsible for developing and maintaining advanced strategic capacity models that predict operational resource demand and providing recommendations to key stakeholders. In addition, the position will assist with efforts to ensure the capacity models adhere to Model Risk Management (MRM) standards. The ideal candidate will have a keen eye for detail, a strong sense for modelling complex operational systems, and excellent verbal and written communication skills.Our team believes in being inclusive and supportive of all people and their unique situations. We embrace diversity and thrive on learning from each other. We share knowledge and experiences. We support a healthy work-life balance and offer competitive benefits (PTO, health insurance, 401K, paternal leave, etc.).

Responsibilities include, but are not limited to:

• Responsible for developing and modernizing volume forecasting and resource optimization models using advanced time series, simulation and optimization techniques.
• Evaluating new opportunities and implementing changes for current capacity model inputs, processes, and outputs
• Design and implement efficiency metrics and insights to provide guidance to the operations and drive budgeting and business decisions
• Assist in driving forecasting and capacity modelling consistency and innovation across team
• Routinely partner with the Front Line Units (FLUs) to generate best in class outcomes
• Lead efforts to adhere to Model Risk Management (MRM) requirements including writing documentation and providing guidance to junior analysts

Required Skills:

• Master’s degree in Industrial Engineering, Mathematics, Statistics, Applied Economics, Operations Research, Advanced Analytics, other STEM field (or comparable infield experience)
• 5+ years of experience in quantitative roles modelling complex systems
• Fundamental understanding of simulation and operations research techniques (discrete event simulation, Monte Carlo simulation, queuing theory, Markov chain modeling, optimization, etc.)Fundamental understanding and experience with Linear Regression/Time Series/Other Statistical Modelling, both through education and professional experience
• Proficient with Arena or similar discrete event simulation software
• Proficient with SAS OR, GAMS, XPRESS, CPLEX, or similar optimization software
• 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

Desired Skills:

• Prior forecasting and capacity or financial planning/modelling experience
• Tableau or other data visualization software experience
• Data mining experience using SQL/SAS querying
• Experience with SAS, Python, R, or similar
• Prior Banking industry analytics and modelling experience, specifically with developing forecasting and capacity or resource optimization models that adhere to standards set by a risk management governing body

Enterprise Role Overview:

Responsible for developing quantitative/analytic models and applications in support of the firm's risk management effort. This role focuses on the development of operations/data management policies, strategies and operational guidelines for the organization's various financial products as they relate to the analysis, tracking, and reporting of various risk metrics. This role often possesses an advanced degree in physic, applied mathematics, statistics/probability or another heavy quantitative discipline. Quantitative analytic staff is focused on and responsible for the development of the theory and mathematics behind various models. May report to either Quant Operations Exec or Quantitative Operations Manager

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