Senior Quantitative Analytics Specialist - Generative and Agentic AI model validation

Job Description
About this role:
Wells Fargo is seeking a Senior Quantitative Analytics Specialist to join its Decision Science and Artificial Intelligence (DSAI) group within Model Risk Management (MRM). The responsibilities of the DSAI Group include end to end responsibility of managing the model risk over the model lifecycle including risk tiering, validation, and performance monitoring etc.
In this specific position, the analyst will focus on models built in house and by third parties with machine learning and AI technologies primarily for the purpose of Natural Language Processing (NLP); Generative AI; and/or Agentic AI. MRM operates in a fast-paced work environment with continuously changing policies and technologies and the ability to multi-task and meet strict timelines is critical.
Learn more about the career areas and lines of business at wellsfargojobs.com.
In this role, you will:

• Support the validation projects and coach junior team members.
• Review analytical data and sampling plans, various modeling frameworks, model replications, model performance assessments, test model development, model monitoring, and provide effective challenge to lines of business.
• Develop reusable code and libraries to accelerate NLP and Gen AI model validation.
• Write detailed standard analytical reports to ensure Wells Fargo's compliance with governance policies and regulations.
• Communicate with stakeholders, regulators, and auditors.

Required Qualifications:

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications:

• A PhD in statistics, computer science, optimization, electrical engineering, or a related quantitative discipline.
• In-depth knowledge of Machine Learning (ML) methodologies such as ensemble algorithms, neural networks, supervised and unsupervised learning.
• In-depth knowledge of Natural Language Processing concepts including transformer architecture and other generative AI technologies.
• Strong computing and programming background and knowledge of one or more languages such as Python and Java
• Experience with ML/AI computing platforms and tools such as PyTorch, TensorFlow and Keras
• Experience with GPU programming, multi-core, or distributed programming.
• Excellent writing and communication skills for documentation and presentations to audiences of all technical backgrounds.
• Ability to work in cross-organizational projects and collaboratively with other groups.
• Be self- motivated, require minimal supervision, and produce work that is consistent with MRM's recognized framework, procedure, and high standards.
• Proficient with MRM framework and procedure.

Job Expectations:

• Ability to travel up to 15% of the time.
• This position offers a hybrid work schedule.
• Willingness to work onsite at stated location on the job posting.
• This position is eligible for VISA sponsorship.

Job Posting Locations:

• Three Wells Fargo Center, CHARLOTTE, NC
• 600 Wells Fargo, MINNEAPOLIS, MN
• Las Colinas Bldg B, Irving Campus, IRVING, TX
• West Des Moines Campus, 800 S Jordan Creek Pkwy, WEST DES MOINES, IA
• D Building,114N Beaumont St -D Bldg., SAINT LOUIS, MO
• 1150 W Washington, TEMPE, AZ
• 333 Market, SAN FRANCISCO, CA

Pay Range
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
$139,000.00 - $260,000.00
Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement

Posting End Date:
21 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.
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.
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