Senior Quantitative Analytics Specialist (#001941)

Wells Fargo & Company•San Francisco, CA

3d•$167,000 - $260,000•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 Business Analytics, Information Management, or related field.
Four (4) years of experience in the job offered or in a related position involving quantitative analytics experience.
Programming languages used for statistical analysis and data programming including SAS, R, C++, Python, SQL, and MATLAB;
Analytical software like 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.

Responsibilities

Perform highly complex activities related to creation, implementation and documentation.
Use highly complex statistical theory to quantify, analyze and manage markets.
Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives.
Utilize structured securities and provide expertise on theory and mathematics behind the data.
Manage market, credit, and operational risks to forecast losses and compute capital requirements.
Participate in the discussion related to analytical strategies, modeling and forecasting methods.
Identify structure to influence global assessments, inclusive of technical, audit and market perspectives.
Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills.