PAY RANGE

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation package offered to candidates.
$185,000.00 - $300,000.00

APPLICANTS WITH DISABILITIES

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .

WELLS FARGO RECRUITMENT AND HIRING REQUIREMENTS:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process

Required Qualifications, US:

• 5+ years of Securities Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, educatio

Desired Qualifications:

• 5+ years in quantitative finance, particularly in rates derivatives modeling and implementation. Familiarity with pricing models, risk analytics, and financial instrument behavior under various market conditions. Exposure to cross-asset model integration and curve construction is a strong plus
• Advanced academic credentials including a Ph.D. in a quantitative discipline such as computer science, statistics, applied mathematics, or physics, or a Master’s in financial mathematics. Candidates should have a strong foundation in machine learning and artificial intelligence demonstrated through research, publications, or enterprise-scale applications.
• Demonstrated success in building, deploying, and maintaining scalable ML/AI models in production environments. Proficiency in managing the full model lifecycle including training, validation, deployment, monitoring, and documentation.
• Proven ability to communicate complex ML/AI concepts clearly to both technical and non-technical audiences.
• Experience collaborating across functions-such as trading desks, risk oversight, and model governance-to align technical solutions with strategic and regulatory goals.
• Extensive hands-on programming experience in C++, Python, and Java

Our Corporate & Investment Banking Front Office Quantitative Model Development Team is working on a strategic buildout initiative. This strategic initiative will enhance our ability to partner and deliver excellent quality and service to our trading and sales partners as our platform continues to grow.
We are seeking a highly skilled and polished ML/AI (Machine Learning/ Automated Intelligence) Specialist as a Vice President to join our team, driving innovation through advanced analytics and intelligent systems. This role is ideal for someone passionate about predictive intelligence and time-aware modeling, with a strong foundation in time series analysis, statistical learning, financial modeling and automation.

In this role, you will:

• Develop and maintain AI-powered forecasting models and pattern discovery frameworks
• Apply statistical learning, machine learning, and artificial intelligence techniques to extract insights from complex datasets.
• Build smart models and time-aware algorithms that adapt to dynamic environments
• Leverage computational intelligence for time series modeling and predictive analytics
• Collaborate across teams to integrate learning machines into business processes.

Required Qualifications, US:

• 5+ years of Securities Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• 5+ years in quantitative finance, particularly in rates derivatives modeling and implementation. Familiarity with pricing models, risk analytics, and financial instrument behavior under various market conditions. Exposure to cross-asset model integration and curve construction is a strong plus
• Advanced academic credentials including a Ph.D. in a quantitative discipline such as computer science, statistics, applied mathematics, or physics, or a Master’s in financial mathematics. Candidates should have a strong foundation in machine learning and artificial intelligence demonstrated through research, publications, or enterprise-scale applications.
• Demonstrated success in building, deploying, and maintaining scalable ML/AI models in production environments. Proficiency in managing the full model lifecycle including training, validation, deployment, monitoring, and documentation.
• Proven ability to communicate complex ML/AI concepts clearly to both technical and non-technical audiences.
• Experience collaborating across functions-such as trading desks, risk oversight, and model governance-to align technical solutions with strategic and regulatory goals.
• Extensive hands-on programming experience in C++, Python, and Java.

Keywords:

• Rates, model, quant, machine learning, automated intelligence, derivatives, trade, time series, automation, predictive modelling