Securities Quantitative Analytics Associate (#001926)

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 Securities Quantitative Analytics Associate in Charlotte, NC.

Job Role and Responsibility:

Participate in less complex initiatives and identify opportunities for process improvements within Securities Quantitative Analytics. Develop automated trading algorithms or create cutting-edge derivative pricing models and empirical models to provide insight into market behavior. Combine mathematical programming and market expertise to build and generate systematic strategies. Review and analyze basic business, operational, or technical assignments or challenges that require evaluation, and a selection of alternatives. Exercise independent judgment to guide medium risk deliverables. Use quantitative and technological techniques to solve complex business problems. Conduct research on trading cost models, liquidity models, risk models, portfolio construction methodology, and signal generation. Present recommendations for resolving more complex situations. Exercise independent judgment while developing expertise in the Securities Quantitative Analytics. Collaborate and consult with colleagues, internal partners, and stakeholders. Play an integral role to the trading floor.

Travel required:  0%

Required Qualifications:

Degree required: PhD in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline.

Amount and type of experience required: 2 years of experience in the job offered or in a related securities quantitative analytics role.  

Specific skills required:

· Stochastic Modeling, Optimization, Simulation, Computational Statistics; · Developing and validating a variety of statistical models including sampling and subsampling methodologies, logistic regression models, time series models, large-scale econometric models, and machine learning models including gradient boost and neural networks; · Conducting advanced time-series analysis on large-scale data and developing models for outlier detection and missing-data imputation; · Experience handling large, complex datasets, and database experience including data querying, processing, and analysis; · Strong quantitative finance skills and understanding of structured products including asset-backed securities and mortgage-backed securities; · Experience with market risk models, including Value-at-Risk (VaR), expected shortfall (ES) and related risk metrics; · Programming languages used for statistical analysis and data programming including SAS, R, C++, Python, SQL, and MATLAB; · Utilizing best modeling practices and methodologies in the areas of data processing, sampling, model design/specification, model performance assessment, and evaluation testing; · Ability to clearly document the development outcomes. Performing model validations and documenting evidence of validation activities to identify conceptual weaknesses in a model and understand tradeoffs with alternate approaches.

Posting End Date: 

25 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.