2023 Wells Fargo Quantitative Analytics Program – Capital Markets (PhD Degree)
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About this role
Wells Fargo is seeking talent to join the Quantitative Analytics Program. Learn more about the career areas and lines of business at wellsfargojobs.com
The Quantitative Analytics Program is a professional development program aimed at Masters and PhD graduates that provides participants with a 12-month orientation to Wells Fargo and an opportunity to gain comprehensive professional industry experience. Utilizing a combination of orientation, classroom training, and professional development activities, we provide an exciting and diverse environment where you will have the ability to tackle interesting and challenging problems. Fellows will work under the supervision of a senior team member to learn how to develop, implement, calibrate, or validate quantitative models for use across Wells Fargo lines of businesses, operations or products. Program participants have the opportunity to influence risk management strategies, interact with senior leaders, excel through individual coaching and mentoring, and participate in team building activities.
The Capital Markets track deals with mathematical models for pricing, hedging and risking complex financial instruments. Wells Fargo trading portfolios include products in all traded asset classes such as credit, commodity, Equity, FX, Rate, Mortgages, and Asset-Backed Finance.
Placement group includes:
· Traded Products Model Development
· Market and Counterparty Risk Analytics
· Mortgage Model Development
· Corporate Model Risk
In this role you will:
· Use Python, R, C++, SAS, SQL or other programming languages as well as mathematical/statistical packages for model development and validation
· Perform mathematical model development and validation (risk assessment) under the direction of experienced team members
· Produce required documentation to evidence model development or validation
· Understand business needs and providing possible solutions through clear verbal and written communications to management and fellow team members
· Stay up to speed on industry challenges and new and innovative modeling techniques used across Wells Fargo to solve business problems or enhance business capabilities.
· Participate in model related projects for varying purposes, methodologies and relevant lines of business
· Provide solutions to business needs and analyze work flow processes to make recommendations for process improvement in risk management
· Collaborate and consult with peers, colleagues, managers and regulators to resolve issues and achieve goals
Program Start Date: July 2023
Program Length: 12 Months (Two, six month rotations)
· 2+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
· Master’s degree or higher in statistics, mathematics, physics, engineering, computer science, economics, or quantitative field
· Enrolled in a PhD program with an expected graduation date in December 2022 – May/June 2023 with emphasis on Statistics, Applied or Computational Mathematics, Computer Science, Economics, Physics, Quantitative Finance, Operations Research, Data Science, Engineering, or related quantitative field.
· Excellent computer programing skills and use of statistical software packages such as Python, R, SAS, SQL, Scala/Spark, Java, and C++
· Strong verbal, written communication and interpersonal skills
· Experience and demonstrated knowledge in mathematical and numerical methods including Monte Carlo methods, differential equations, linear algebra, applied probability, and statistics
Program Location: Charlotte, NC; Additional locations may be added based on business needs.
How to Apply:
The 2023 Wells Fargo Quantitative Analytics Program will be accepting applications through the Wells Fargo Career website on September 12 – 26, 2022 ONLY.
· Search by Req#: R-197949 or by keywords, “Wells Fargo Quantitative Analytics Program” and follow the instructions to complete your application.