Lead Quantitative Analytics Specialist - AI Innovation & Modeling (AIM)

Wells Fargo Bank•Charlotte, NC

1d•Hybrid

About The Position

Wells Fargo is seeking a Lead Quantitative Analytics Specialist in the AI Innovation & Modeling (AIM) group under the COO – Data, Analytics and AI. The role drives generative AI (GenAI) and large language model (LLM) initiatives, translating emerging AI capabilities into scalable, ethical, high-impact applications that align with enterprise goals and regulatory standards. It guides cross-functional execution and supports the integrity and performance of quantitative models used in real-time decision-making across the COO organization. The specialist leads the design, development, implementation, and operationalization of machine learning, GenAI, and LLM systems, including solutions for complex language-understanding tasks. The role also promotes technical excellence, collaboration, responsible model practices, and practical application of emerging research. The position is based in Charlotte, North Carolina, with a hybrid schedule of three days onsite and two days remote. Travel of up to 10% may be required. Remote work locations are not available; candidates outside a listed location must commit to relocating within an agreed timeframe. The position is not eligible for visa sponsorship.

Requirements

At least 5 years of quantitative analytics experience, or equivalent demonstrated through work experience, training, military experience, or education.
A master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Ability to work onsite according to the hybrid operating model: three days onsite and two days remote.
Ability to travel up to 10% of the time.
Must commit to self-relocation within an agreed timeframe if not currently in a listed location.

Nice To Haves

Hands-on experience with GenAI frameworks and tools, such as Google ADK or LangChain.
Deep understanding of machine learning, LLMs, and GenAI technologies.
Experience with responsible AI practices and regulatory alignment.
Strong Python programming skills.
Demonstrated experience fine-tuning and deploying LLMs.
Experience with prompt engineering and optimization techniques.
Knowledge of model-evaluation metrics and performance optimization.
Experience with multimodal models and retrieval-augmented generation.
Contributions to open-source ML/NLP/LLM projects or research publications.
Experience with MLOps and model-deployment pipelines.
Experience with cloud platforms such as GCP or Azure for ML workloads.
Background in banking, finance, or related domain applications.
Experience with distributed computing for large-scale model training.
Experience leading technical teams and managing complex projects.
Strong strategic, communication, and collaboration skills.

Responsibilities

Lead the design, development, and implementation of machine-learning, GenAI, and LLM-based systems for complex language-understanding tasks.
Architect scalable and robust solutions using state-of-the-art machine-learning and GenAI techniques, open-source tools, or vendor frameworks.
Guide and mentor junior team members, fostering technical excellence and collaboration.
Partner with cross-functional teams to gather requirements and deliver AI-driven solutions.
Engage with validators, auditors, and technical stakeholders to ensure transparency and compliance.
Monitor emerging machine-learning, LLM, and GenAI trends and translate research into practical applications.
Drive innovation through proof-of-concept initiatives and exploratory research.
Establish and promote best practices for model development, evaluation, and deployment.
Build and operationalize AI/ML models using state-of-the-art libraries and cloud-native tools.