Quantitative Analytics Specialist (002136)

Wells Fargo Bank • Charlotte, NC

11d • Hybrid

About The Position

Corporate Risk helps all Wells Fargo businesses identify and manage risk. The team focuses on several key risk types, including conduct, credit, financial crimes, information security, interest rate, liquidity, market, model, operational, regulatory compliance, reputation, strategic, and technology risk. The group provides leadership, enhances communications, assists with problem identification and solutions, and shares best practices. In addition, the group provides an enterprise-wide view of risk, assists management and our Board of Directors in identifying and monitoring risks that may affect multiple lines of business, and takes appropriate action when business activities exceed the risk tolerance of the company.

Requirements

• Master's degree in Mathematics, Statistics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline plus 2 years of experience in the job offered or in a related quantitative analytics role.
• Alternatively, a PhD in Mathematics, Statistics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline plus 0 years of experience.
• Experience in at least 4 of the following: Programming languages used for statistical analysis and data programming including SAS, R, C++, Python, SQL, and MATLAB; Analytical software Hadoop and NoSQL; Linux and Unix Operating Systems; Predictive modeling using statistical and machine learning techniques; Stochastic Modeling, Optimization, Simulation, Computational Statistics, and Machine Learning; Statistical model development/validation; Documenting and presenting detailed model development and validation outcomes and results; Utilizing best modeling practices and methodologies in the areas of data processing, sampling, model design/specification, model performance assessment, and evaluation testing; Application of analytical, statistical and forecasting methods with focus on the theory and mathematics behind the analyses; Performing model validations and clearly documenting evidence of validation activities to identify conceptual weaknesses in a model and understand tradeoffs with alternate approaches; Providing effective challenges to models developed in lines of business to reduce model risk to meet or exceed regulatory and industry standards; Developing and validating a variety of statistical, machine learning and Artificial Intelligence (AI) models, including hazard models, logistic regression models, time series models, large-scale econometric models, and gradient boosting machines; Working within the regulatory framework for financial institutions and interfacing with regulators and auditors.

Responsibilities

• Develop, implement, and calibrate various analytical models.
• Perform highly complex activities related to financial products, business analysis and modeling.
• Perform basic statistical and mathematical models using Python, R, SAS, 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.
• Collaborate and consult with peers, colleagues, managers, and regulators to resolve issues and achieve goals.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior