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

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About this role:
Wells Fargo is seeking a Lead Quantitative Analytics Specialist within the AI Innovation & Modeling (AIM) group under the COO - Data, Analytics and AI, to drive our GenAI and large language model initiatives. This role is pivotal in translating cutting-edge AI and GenAI capabilities into scalable, ethical, and high-impact use cases that align with enterprise goals and regulatory standards.
You will be responsible for guiding cross-functional execution, collaborating with stakeholders, and ensuring the integrity and performance of quantitative models used in real-time decision-making. Your work will directly influence the quality and reliability of model-based analytics and technology solutions across the COO organization.
In this role, you will:

• Lead the design, development, and implementation of Machine Learning (ML), 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 and open-source or vendor frameworks.
• Guide and mentor junior team members, fostering technical excellence and collaboration.
• Partner with cross-functional teams to gather requirements and deliver impactful AI-driven solutions.
• Engage with validators, auditors, and technical stakeholders to ensure transparency and compliance.
• Stay abreast of emerging trends in Machine Learning, LLMs, and GenAI, 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.

Required Qualifications:

• 5+ 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:

• Hands-on experience with GenAI framework (e.g., Google ADK, Langchain) and tools.
• Deep understanding of ML, LLMs, and GenAI technologies.
• Experience in responsible AI practices and regulatory alignment.
• Strong programming skills in Python.
• 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 (GCP, Azure) for ML workloads.
• Background in specific domain applications (banking, finance, etc.).
• Experience with distributed computing for large-scale model training.
• Experience leading technical teams and managing complex projects.
• Strong strategic, communication, and collaboration skills.

Job Expectations:

• This position is NOT eligible for Visa sponsorship.
• Ability to work on site per Wells Fargo's standard operating model in the listed location (hybrid schedule - 3 days on-site & 2 remote).
• The ability to travel up to 10% of the time.

Posting Location:

• Charlotte, NC

** The Chief Operations Office (COO) functions adhere to a location strategy; therefore, your candidacy may be determined based on your current location. Remote work locations are not available for these roles, so if you are not in a location listed on the posting, you must commit to self-relocation within an agreed upon timeframe. **
Posting End Date:
19 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.
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