2027 Quantitative Analytics Summer Internship Capital Markets (PhD) – Early Careers

Wells Fargo is seeking PhD candidates to join the 2027 Quantitative Analytics Summer Internship Program within Capital Markets.

About the Program

The Wells Fargo Quantitative Analytics Internship Program offers PhD candidates a 10-week summer internship to apply advanced analytics, artificial intelligence, and machine learning to complex business challenges at a leading financial institution. The program combines hands-on project experience, mentorship, technical training, and exposure to senior leaders.

Interns will work alongside experienced quantitative professionals to develop and evaluate innovative solutions supporting business strategy, risk management, and customer experience. High-performing interns may receive consideration for full-time roles after graduation.

Responsibilities

• Develop pricing models used by Wells Fargo trading desks
• Enhance production models to mitigate performance deterioration
• Develop simulation models to forecast losses for trading portfolios
• Create benchmark models to assess limitations of production models
• Provide analysis and reporting of metrics for ongoing model performance
• Apply statistical and quantitative techniques to validate model design, calibration, and implementation

What You’ll Experience

• Spend your Intern Induction Week at an offsite location
• Structured and engaging onboarding experience
• Speaker series with Wells Fargo senior leaders
• Professional development opportunities
• Networking and engagement with peers
• On-the-job experiences contributing to strategic business goals

Program dates: June – August 2027
Program duration: 10 weeks
Program location: Charlotte, NC

Requirements

2+ years of work experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, or education.

Qualifications

• Currently pursuing a PhD in Mathematics, Physics, Engineering, Statistics, or a related quantitative field, with an expected graduation date after December 2027
• Excellent programming skills for data and statistical analysis (e.g., Python, C++, SQL, Java)
• Experience and demonstrated knowledge in mathematical and numerical methods, including Monte Carlo methods, differential equations, linear algebra, applied probability, and statistics
• Strong quantitative and analytical skills, with the ability to apply data analysis, modeling, visualization, statistics, research, and generative AI to generate insights and support innovative solutions
• Ability to execute with urgency, apply data and software engineering skills to design and deliver scalable solutions, and drive operational excellence with strong data management and an enterprise mindset
• Strong communication skills, with the ability to foster an inclusive environment and actively seek, apply, and respond to feedback in collaborative analytical settings
• Strong business acumen and understanding of capital markets, with a commitment to providing excellent service and supporting data-informed business outcomes
• Ability to act with integrity, support risk assessments, and apply risk controls to help manage risk in a disciplined, data-driven environment