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