2027 Quantitative Analytics Summer Internship Applied Computational Intelligence (ACI Masters) – Early Careers

About the role

Wells Fargo's 2027 Quantitative Analytics Summer Internship offers Masters candidates a 10-week program to apply AI, machine learning, and advanced analytics to business challenges. Interns gain hands-on experience, mentorship, and exposure to senior leaders in Charlotte, NC.

Program Overview

• 10-week summer internship from June to August 2027 in Charlotte, NC.
• Apply advanced analytics, AI, and machine learning to financial business challenges.
• Work alongside experienced quantitative professionals on impactful projects.
• Develop technical, business acumen, and leadership skills in a collaborative environment.
• High-performing interns may be considered for full-time roles after graduation.

Key Projects

• Develop AI-powered advisors and decision support systems using enterprise data.
• Build Generative AI assistants and intelligent agents for employees and customers.
• Design agentic AI and multi-agent systems for automating business processes.
• Create knowledge intelligence platforms using LLMs, RAG, and multimodal AI.
• Advance enterprise AI through model training, evaluation, and deployment.
• Deploy scalable AI and machine learning solutions to improve productivity and risk management.

Experience and Training

• Intern Induction Week at an offsite location with structured onboarding.
• Speaker series featuring Wells Fargo senior leaders.
• Professional development and networking opportunities.
• On-the-job experience contributing to strategic business goals.

Requirements

• 6+ months of work experience or equivalent through education or training.
• Currently pursuing a Masters in Computer Science, Statistics, Data Science, Econometrics, Mathematics, Engineering, or related field.
• Expected graduation after December 2027.
• Strong programming skills in Python, Go, C++, Rust, Java, Spark, or similar.
• Experience developing machine learning and AI solutions in research or industry.
• Knowledge of LLM training, agentic AI frameworks, RAG applications, and AI infrastructure.

Additional Qualifications

• Strong quantitative and analytical skills with data analysis and generative AI.
• Ability to design and deliver scalable data and software engineering solutions.
• Strong communication skills and ability to foster inclusive collaboration.
• Business acumen with commitment to data-informed outcomes and risk management.
• Ability to act with integrity and support risk controls in a data-driven environment.