Quantitative Analytics Specialist (#001887)

At Wells Fargo, we want to satisfy our customers' financial needs and help them succeed financially. We're looking for talented people who will put our customers at the center of everything we do. Help us build a better Wells Fargo.

About the Role

Wells Fargo Bank N.A. seeks a Quantitative Analytics Specialist in Charlotte, NC. Telecommuting is permitted up to 2 days a week. The position must appear in person to the location listed as the work address. Travel required: 0%.

Responsibilities

• Develop state-of-the-art methods in quantitative modeling using statistical and machine learning (ML) techniques and implement them in efficient/scalable algorithms.
• Identify cutting-edge techniques in academia and industry and implement them for applications in risk management.
• Drive the development of methodology and algorithms by conducting applied research.
• Disseminate best practices across the quantitative modeling community within the bank.
• Develop a model library to support the validation process.
• Design benchmark models and implement and automate their use within our advanced computing platform.
• Collaborate with internal and external quantitative communities to keep abreast of the latest developments and practices in quantitative risk.
• Facilitate credible challenge of processes/models and develop the skills of the validation team.
• Build collaborative working environments, including leading process improvement projects.
• Develop, implement, and calibrate various analytical models.
• Perform highly complex activities related to financial products, business analysis, and modeling.
• Build basic statistical and mathematical models using Python, R, C++, and SQL.
• Perform analytical support and provide insights regarding a wide array of business initiatives.
• Provide solutions to business needs and analyze workflow processes to make recommendations for process improvement in risk management.

Requirements

• Master's degree in Finance, Econometrics, or a related discipline.
• 2 years of experience in the job offered or in a related quantitative analytics role. Experience can be gained concurrently with graduate-level coursework.

Skills

• Experience in modeling (statistical and machine learning), optimization, algorithm development, programming, and coding, including:
  • Generalized Linear Models, Gradient Boosting Machines, or Random Forests.
  • The related training and optimization algorithms, and their common implementations in R and/or Python.
• In-depth knowledge of Machine Learning/Deep Learning algorithms and their implementation, such as:
  • XGBoost or LightGBM.
  • Neural Networks, including Multilayer Perceptrons or Convolutional Neural Networks.
• Strong computing and programming background and knowledge of one or more languages including Python, Java, or R.
• Experience with Machine Learning/Artificial Intelligence computing platforms and tools such as TensorFlow and Keras.
• Experience with Graphics Processing Unit (GPU) programming, multi-core, or distributed programming.
• Ability to work with large datasets and experience in database management and tools such as Hadoop, Spark, or SQL.

Reference Number: R-567687