Quantitative Analytics Specialist (001890)

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. Join our diverse and inclusive team where you’ll feel valued and inspired to contribute your unique skills and experience.

Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.

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.

Wells Fargo Bank N.A. seeks a Quantitative Analytics Specialist in Charlotte, NC.

Job Role and Responsibility:

Wells Fargo’s Corporate Model Risk (CMoR) organization is seeking a highly qualified person to join its Advanced Technologies for Modeling (AToM) Group as a Quantitative Analytics Specialist (QAS). The responsibilities of the AToM Group include development of cutting-edge models, algorithms, visualization tools, and computing environment to advance the Bank’s practices in the areas of credit, operational, and market risk management. This individual will be involved in the development of state-of-the-art methods in statistical modeling, machine learning (ML), and optimization as well as implementing them in fast and efficient algorithms. Specific duties include the following: Conducting applied research to drive the development of methodology and algorithms; Identifying state-of-the-art techniques in modeling (statistics and ML) as well as optimization for application in risk management; Implementing the techniques in fast and scalable algorithms in our advanced computing platform; Disseminating best practice across the quantitative modeling community within the bank; Developing model library to support model risk assessment; and Collaborating with internal and external quantitative communities to keep abreast of latest developments and practices in quantitative risk. Telecommuting is permitted up to 2 days a week. Position must appear in person to the location listed as the work address.

Travel required: None

Required Qualifications:

A master’s degree in Statistics, Computer Science, Economics, Electrical Engineering, or a related quantitative field and 2 years of experience in the job offered or in a related quantitative analytics role. Alternatively, a Doctorate (PhD) degree in statistics, computer science, economics, electrical engineering, or a related quantitative field will be accepted.

Specific skills required:

• 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 and 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.

Posting End Date: 

25 Apr 2025

*Job posting may come down early due to volume of applicants.

We Value Diversity

At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those