Level

Wells Fargo

Agentic AI Senior Lead Data Scientist

AI in this role

pytorchtensorflow
nlp

About this role:

Wells Fargo is seeking Agentic AI Senior Lead Data Scientist role as part of the Consumer Model Development CoE. This role is pivotal in leading the development and implementation of cutting-edge Generative AI (GenAI) and Natural Language Processing (NLP) solutions within the Consumer LOB's - Banking, Lending, and WIM divisions.

 

The successful candidate will lead model development for projects/programs and guide a team of data scientists and collaborate with business and technology partners to drive end-to-end solution design and development for implementing virtual assistants, content generation, agentic frameworks, and others for improving employee/customer experience, driving operational efficiencies, and mitigating risks. 

 

Learn more about the career areas and lines of business at wellsfargojobs.com.

 

In this role, you will:

  • Lead the design, development, and deployment of Agentic AI and NLP/ML models for various consumer-facing applications
  • Translate business problems into technical solutions, leveraging advanced GenAI/NLP/ML methodologies
  • Collaborate with cross-functional teams to integrate AI solutions into business processes, ensuring scalability and robustness
  • Provide mentorship and technical guidance to junior data scientists
  • Engage with business stakeholders to communicate insights, model outcomes, and the strategic value of AI initiatives
  • Ensure compliance with regulatory requirements and internal risk management policies

 

Required Qualifications: 

  • 7+ 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
  • Demonstrated expertise in leading Agentic AI projects/programs, including large language models, Generative AI frameworks, and advanced NLP techniques which includes leading GenAI projects from conception to production 

 

Desired Qualifications:

  • Master's degree or higher in a quantitative field such as Computer or Data Science
  • Strong full stack agentic AI skills
  • Strong background in GenAi/NLP, machine learning, deep learning, and statistical analysis
  • Strong collaboration, coaching, communication and presentation skills with the ability to translate complex technical concepts to non-technical stakeholders
  • Proficiency in Python, PySpark, TensorFlow, PyTorch, and cloud platforms such as Google Cloud Platform (GCP),
  • Experience in the financial services industry, particularly within consumer banking, lending, wealth and asset management
  • Familiarity with regulatory and compliance considerations in AI model deployment
  • A track record of published research or patents in AI/ML

 

Job Expectations:

  • Ability to travel up to 10% of the time.
  • This position offers a hybrid work schedule.

Posting Location(s):  

  • 401 S Tryon St. – Charlotte, North Carolina 28202

 

Required locations listed. 

Posting End Date: 

16 Oct 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.

How we rate this

Agentic AI Senior Lead Data Scientist at Wells Fargo rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

NLPPyTorchTensorFlow

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: NLP, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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