Senior Lead Quantitative Analytics Specialist

Location: IRVING, TX

Time Type: Full time

Job Description

About this role:

Wells Fargo is seeking a Senior Lead Quantitative Analytics Specialist to serve as a strategic advisor and technical authority driving the development, governance, and deployment of highly complex quantitative and advanced analytics solutions, and advancing GenAI and Agentic AI capabilities across Commercial Banking. This role sits within Commercial Banking Model Development Center and works in close partnership with Technology, Business, Product, and Risk organizations. This role is pivotal in accelerating the building and adoption of Generative AI and Agentic AI capabilities, providing strategic vision and technical leadership to ensure solutions are robust, scalable, and aligned with regulatory and market expectations.
 

This leader will bring scientific rigor, structured experimentation, and model risk discipline to our GenAI initiatives, ensuring our AI systems are measurable, explainable, responsible, and continuously improving.

In this role, you will conduct:

Experimentation & Evaluation

• Drive the development and evaluation of Generative AI and Agentic AI solutions aligned with regulatory, audit, and market expectations
• Design and lead experiments for GenAI and Agnetic AI use cases
• Define clear success metrics and evaluation frameworks (quality, hallucination detection, bias, robustness, agent reliability, etc.)
• Design and implement LLM evaluation frameworks, guardrails, controls, and performance monitoring to ensure reliable and compliant model behavior
• Conduct error attribution and failure analysis to understand, prevent, and manage agent and model performance issues
• Conduct complex analysis to determine performance drivers and trade-offs
• Perform root-cause analysis of model failures and degradation
• Translate experimental findings into actional implementation requirements for Technology

Collaboration & Partnership

• Partner with Business, Technology, Data, and Risk teams to deliver end‑to‑end AI systems
• Partner closely with Business and AI Product teams to define solutions, conduct experiments, and build out POCs and MVPs in deployable parity environments
• Partner closely with Tech teams on system architecture, engineering framework, deployment options, ensuring solutions are testable, observable, and measurable, ensure alignment between experimental prototypes and production environments
•  Partner on integrating guardrails, monitoring, and feedback loops into systems

AI Risk & Governance

• Develop testing protocols addressing bias, explainability, stability, drift, and operational risk
• Partner with Model Risk, Compliance, and Audit to ensure responsible AI deployment, to support transparency, governance, and compliance for quantitative and AI models
• Document methodologies and development processes to support governance standards
• Implement monitoring strategies that proactively identify model and agent risks

Strategy & Team Leadership

• Lead and mentor a pod of data scientists to engineer context, orchestrate agent workflows, and build scalable AI solutions
• Establish experimentation standards and scientific best practices
• Advise senior leadership on AI performance, limitations, and risk posture
• Identify high impact GenAI opportunities grounded in measurable outcomes.

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
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications:

• Experience leading technical teams or pods
• Strong expertise in:
  • GenAI experiment design and inference
  • LLM evaluation methodologies and frameworks
  • Model performance diagnostics and failure analysis
• Experience working with Tech/engineering teams to deploy experimental work into production systems
• Strong full stack data science skills, hands on experience with ADK, MCP, A2A, O2A. LLM evaluation framework, design and develop LLM guardrails, assertions, controls, and performance monitoring
• Advanced proficiency in Python, PySpark, TensorFlow, PyTorch, and cloud platforms including Google Cloud Platform (GCP), Vertex AI, Google ADK, and MCP
• Strong background in GenAI, Agentic workflow, machine learning, deep learning, and statistical analysis evidenced by successful deployment at scale
• Experience working with LLM-based systems (RAG, tool-use, multi-agent systems)
• Experience with AI observability and evaluation tooling
• Experience in the financial services industry or other highly regulated industries, Commercial Banking a plus
• Familiarity with regulatory, risk, and compliance considerations related to AI and GenAI model development and deployment
• Strong communication skills with the ability to influence technical and executive audience

Job Expectations:

• This position is not eligible for Visa sponsorship 
• This position offers a hybrid work schedule 
• Specific compliance policies may apply regarding outside activities or personal investing; affected employees will be expected to provide information to the Wells Fargo Personal Account Dealing Team and abide by applicable policy requirements if hired. Information will be shared about expectations during the recruitment process 
• Ability to travel up to 10% of the time 
  #commercialbanking 

Locations:

• 401 Las Colinas Blvd W - Irving, Texas 75039
• 2700 South Price Road - Chandler, Arizona 85286
• 333 Market Street - San Francisco, California 94105
• 600 South 4th Street - Minneapolis, Minnesota 55415
• 550 South Tryon Street - Charlotte, North Carolina 28202

Pay Range:

• $185,000 - $300,000 USD annual
• Eligible for discretionary annual bonus

Posting End Date: 

*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.