Quantitative Analytics Manager

About this role:
Wells Fargo is seeking a Quantitative Analytics Manager.
Wells Fargo is seeking a hands-on Manager for oversight of development of Foundation models as well as Gen AI and Agentic applications supporting the bank across various lines of business.
Model, Methodology and Research (MMR) Team: MMR is a specialized team which supports high priority research and development activities across Front line and second line teams within the bank. Team supports various strategic initiatives including development of Gen AI applications, in-house Large Language models, research for cutting-edge development in the industry, and Agentic development. Team also publish research papers in the top-tier conferences such as NeurIPS or ICLR.
In this role, you will:

• Manage a team responsible for the creation and implementation of low to moderate complex financial areas
• Mitigate operational risk and compute capital requirements
• Determine scope and prioritization of work in consultation with experienced management
• Participate in the development of strategy, policies, procedures, and organizational controls with model users, developers, validators, and technology
• Make decisions and resolve issues regarding operational risks and enable decision making in business, product, marketing, or other functional areas
• Manage a team comprised of quantitative analysts and credit risk analysts
• Interact with internal and external audit or regulators
• Manage allocation of people and financial resources for Quantitative Analytics
• Mentor and guide talent development of direct reports and assist in hiring talent

Required Qualifications:

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

Desired Qualifications:

• Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, Engineering or related quantitative field
• 5+ years of experience in AI/ML model development
• 2+ years of experience building Foundation Models, Gen AI and Agentic AI applications
• Strong quantitative and analytical skills, with the ability to apply data analysis, modeling, visualization, statistics, research, and generative AI to generate insights, adapt quickly, and support innovative solutions.
• Ability to execute with urgency, apply data and software engineering skills to design, develop, and deliver scalable solutions, and drive operational excellence with strong data management and an enterprise mindset.
• Strong communication skills, with the ability to foster an inclusive environment and actively seek, apply, and respond to feedback in collaborative analytical settings.
• Strong business acumen with a commitment to providing excellent service and supporting data-informed business outcomes.
• Ability to act with integrity, support risk assessments, and apply risk controls to help manage risk in a disciplined, data-driven environment.

Knowledge and Experience in:
Foundation Model Training

• Experience with pre-training, supervised fine-tuning (SFT) and post-training methodologies including RLHF, RLAIF, PPO, DPO, and GRPO
• Training and deploying models in cloud environments, including GCP

Agentic AI

• Multi-agent architectures and orchestration frameworks like LangChain, LangGraph, LangChain, LlamaIndex, Google's ADK, CrewAI
• Retrieval-Augmented Generation (RAG) applications and intelligent agent deployment

AI Infrastructure & Optimization

• Distributed GPU training
• Efficient model tuning approaches such as LoRA and PEFT

Job Expectations:
You will be hands-on working and delivering high-impact projects involving foundation models, large language models, multi-agent workflows, retrieval-augmented generation, human-in-the-loop AI, model evaluation, automation, and responsible AI deployment at enterprise scale. In addition, you will also lead a team working on building Agentic and Gen AI applications.

• Design, pre-train, fine-tune, and evaluate transformer-based, foundation, and small language models (SLMs).
• Develop and deploy AI and machine learning solutions across generative AI, agentic systems, and traditional machine learning applications
• Design and build LLM-powered agents and multi-agent systems capable of planning, reasoning, task orchestration, and human-in-the-loop collaboration
• Monitor production models and AI systems, evaluating performance, stability, and model drift through testing and analytics frameworks
• Collaborate with cross-functional teams, technical experts, and business leaders across the organization
• Gain exposure to enterprise-scale AI development, governance, and risk management practices
• Apply AI, machine learning, and generative AI techniques to solve complex business problems.
• Build and optimize scalable model training and deployment pipelines.
• Leverage distributed computing and advanced training techniques to improve model performance and efficiency.
• Enhance model performance through distillation, quantization, and pruning.
• Optimize inference speed, latency, throughout, and cost for production AI systems.

Posting End Date:
29 Sep 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.