Lead Quantitative Analytics Specialist (#001756)

Wells Fargo

Hybrid

Quick summary

Work type
Hybrid
Location
New York, NY
Salary
$191,000–$305,000 / yr
Posted
2 days ago
Closes
Jul 7, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $163k
This role $248k
$104k most similar roles pay here $327k

This role pays more than 91% of similar roles. Most pay $129,241–$197,287 — the shaded band above. At the midpoint, this role pays about $248k versus about $163k 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 90 open roles on FindRole.

Listed pay typically runs $144,009–$224,000 across 50 roles with salary data.

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At a glance

TL;DR · Lead Quantitative Analytics Specialist (#001756)

Wells Fargo Bank N.A. is seeking a Lead Quantitative Analytics Specialist to join their New York-based team, where you will lead complex initiatives involving statistical theory creation and implementation, market monitoring, risk forecasting, and model validation. Your day-to-day responsibilities include developing AI/ML models using Python, PySpark, and PyTorch, collaborating with business leaders to frame problems and explore ML/DL architectures, and ensuring compliance with corporate model risk policies. You will work in an agile environment, operationalizing models for production use while sharing knowledge on cutting-edge NLP/ML/DL algorithms within the organization. The role requires a Master’s degree in Mathematics, Statistics, or related fields, along with five years of experience in quantitative analytics and expertise in Python, Spark, SQL, Hadoop, and machine learning techniques.

What you'll do

  • Lead the creation, implementation, and validation of complex statistical theories for risk management.
  • Forecast credit and operational risks by analyzing market data and trends.
  • Develop and deploy AI/ML models using Python, PySpark, and other state-of-the-art tools.
  • Collaborate with regulators to ensure compliance with model risk management policies.
  • Present analytical results and strategies to stakeholders and consult on regulatory matters.
  • Identify and gather modeling artifacts for repeatable processes in data science projects.

What we're looking for

  • Master's degree in Mathematics, Statistics, or related quantitative field required
  • Five years of experience in quantitative analytics or similar role
  • Expertise in statistical modeling, machine learning, and natural language processing
  • Proficiency in Python, Spark, SQL, and Hadoop/Big Data technologies
  • Ability to design, develop, and deploy AI/ML models using state-of-the-art techniques
  • Experience collaborating with regulators and auditors on model validation and documentation

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