Quantitative Analytics Specialist - NLP and GEN AI

Wells Fargo • Irving, TX

1d • Hybrid

About The Position

Wells Fargo is seeking a Quantitative Analytics Specialist within the AI Innovation & Modeling (AIM) group under the Chief Administrative Office (CAO). You will focus on NLP and GenAI model delivery across multiple Line of Business. Utilizing cutting-edge AI and GenAI, this role is essential in building scalable, ethical, and high-impact use cases that align with enterprise goals and regulatory standards. In this role, you will: Perform highly complex activities related to product analytics, statistical and AI modeling Build GenAI applications: Implement retrieval‑augmented generation (RAG), tool‑use/function‑calling, and multi‑step planning using modern LLM stacks (e.g., OpenAI SDK, Hugging Face, Anthropic, or similar). Build engineer AI agents: Design task‑oriented and autonomous agents that safely orchestrate tools/APIs, reason over context, and manage memory; implement guardrails. Evaluation & safety: Define success metrics; build offline/online evals; design A/B tests, red‑team scenarios, and feedback loops. Security & compliance: Implement privacy controls, PII handling, content filters, RBAC/ABAC, and audited already telemetry aligned to enterprise standards. Partner & deliver collaborate and coordinate with product, Technology, model risk, and platform teams. Operate within risk, controls and compliance framework, e.g., document robust model lifecycle artifacts

Requirements

• 2+ 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 statistics, mathematics, physics, engineering, computer science, economics, or quantitative discipline

Nice To Haves

• Strong in Python and scripting language
• Hands‑on with LLM application development (prompts, RAG, function‑calling/agents) and modern frameworks (e.g., LangChain/LlamaIndex, OpenAI SDKs).
• Practical knowledge of vector databases/embeddings, tokenization, prompt optimization, and latency/cost tuning.
• Familiarity with AI safety/Responsible AI practices (guardrails, content filtering, red‑teaming, bias considerations).
• 2+ years building LLM‑powered systems in production.
• Experience designing agentic workflows (planning, tools, memory, multi‑agent collaboration) and hierarchical or supervisor models.
• Experience with information retrieval (BM25/splade, hybrid search), document processing (OCR, PDF/HTML parsers), and evaluation datasets.
• Regulated‑industry experience and partnering with risk/compliance/legal on model governance.

Responsibilities

• Perform highly complex activities related to product analytics, statistical and AI modeling
• Build GenAI applications: Implement retrieval‑augmented generation (RAG), tool‑use/function‑calling, and multi‑step planning using modern LLM stacks (e.g., OpenAI SDK, Hugging Face, Anthropic, or similar).
• Build engineer AI agents: Design task‑oriented and autonomous agents that safely orchestrate tools/APIs, reason over context, and manage memory; implement guardrails.
• Evaluation & safety: Define success metrics; build offline/online evals; design A/B tests, red‑team scenarios, and feedback loops.
• Security & compliance: Implement privacy controls, PII handling, content filters, RBAC/ABAC, and audited already telemetry aligned to enterprise standards.
• Partner & deliver collaborate and coordinate with product, Technology, model risk, and platform teams.
• Operate within risk, controls and compliance framework, e.g., document robust model lifecycle artifacts

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees