Lead Quantitative Analytics Specialist - Agentic AI Systems & Platforms

Wells Fargo

Hybrid

Quick summary

Work type
Hybrid
Location
Charlotte, NC · Minneapolis, MN · Irving, TX · West Des Moines, IA · Saint Louis, MO · Tempe, AZ · San Francisco, CA
Salary
$159,000–$305,000 / yr
Posted
3 days ago
Closes
Jun 12, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $201k
This role $232k
$134k most similar roles pay here $323k

This role pays more than 70% of similar roles. Most pay $161,875–$239,902 — the shaded band above. At the midpoint, this role pays about $232k versus about $201k for comparable roles.

Based on 240 similar postings.

Employer

About Wells Fargo

Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services

Wells Fargo currently has 62 open roles on FindRole.

Listed pay typically runs $119,000–$224,000 across 33 roles with salary data.

Most-posted roles

View all roles at Wells Fargo

At a glance

TL;DR · Lead Quantitative Analytics Specialist - Agentic AI Systems & Platforms

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Wells Fargo is hiring a Lead Quantitative Analytics Specialist to join its Frontier AI Model Methodology team, where you will design and develop the Enterprise Model Validation platform and AI agents for real-time model testing and monitoring. This role involves hands-on technical leadership in architecting cloud-native solutions on Google Cloud Platform (GCP) and collaborating with technology teams to ensure production readiness and scalability. You will also work closely with Model Risk Management and Development teams, translating complex requirements into robust technical solutions while championing engineering best practices such as reliability, observability, security, and maintainability. Ideal candidates have a Master’s degree in a quantitative field and 5+ years of experience, along with strong proficiency in Python and hands-on software development skills for production-grade platforms. Experience with agentic AI systems and financial services model risk is highly desired.

Skills

Python Google Cloud Platform (GCP) Kubernetes Docker CI/CD Prometheus Grafana PostgreSQL Apache Kafka GenAI GitHub Copilot Model Risk Management Cloud-Native Solutions Agentic AI Systems Large Language Models Reasoning Models Reliability Engineering Observability Practices Security Best Practices Maintainability Standards

What you'll do

  • Design, build, and deliver an industry-leading Enterprise Model Validation platform with a focus on production readiness and scalability.
  • Architect AI agentic solutions in cloud-native environments like Google Cloud Platform for real-time processing and large-scale systems.
  • Act as a senior engineer by contributing code across the stack including design, development, testing, deployment, and iteration.
  • Provide technical leadership through architecture reviews and implementation to set high engineering standards.
  • Translate complex model risk requirements into robust automated solutions governed by AI agents.

What we're looking for

  • 5+ years of quantitative analytics experience or equivalent
  • Master's degree in a quantitative discipline (mathematics, statistics, etc.)
  • Strong hands-on software development skills with Python
  • Experience building production-grade platforms and AI agentic solutions
  • Proficiency in designing cloud-native systems on GCP
  • Ability to collaborate effectively across model developers, validators, and technology teams
  • Proven track record of technical leadership and influencing platform direction

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