Quantitative Analytics Specialist (002152)

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. 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:

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. Telecommuting is permitted up to 2 days per week. Position must appear in person to the location listed as the work address.

Travel required: 0%

Required Qualifications:

Position requires a Master's degree in Statistics, Mathematics, 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. Will alternatively accept a PhD in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline plus 0 years of experience.

Specific skills required:

Skills can be gained through work experience or graduate level coursework.

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.

Posting End Date:

26 Aug 2026

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

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.