CHARLOTTE, NC, USA
1 day ago
Lead Quantitative Analytics Specialist- Vice President -Natural Language Processing (NLP) and/or Generative AI

About this role:

Wells Fargo is seeking a Lead Quantitative Analytics Specialist - Vice President 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) and/or Generative 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:

​Lead 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:

5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Master'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 locations:

Three Wells Fargo Center, 401 S Tryon St, CHARLOTTE, NC

600 Wells Fargo, Minneapolis, 600 S 4th St, MINNEAPOLIS, MN

Las Colinas Bldg B, 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

Pay Range
 

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation package offered to candidates.

$159,000.00 - $279,000.00

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 benefits401(k) PlanPaid time offDisability benefitsLife insurance, critical illness insurance, and accident insuranceParental leaveCritical caregiving leaveDiscounts and savingsCommuter benefitsTuition reimbursementScholarships for dependent childrenAdoption reimbursement

Posting End Date:

22 Aug 2025

*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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