2026-2027 Wells Fargo Corporate Risk Externship Program (Masters) - Early Careers

About this role: Wells Fargo is seeking talent to join the2026-2027 Wells Fargo Corporate Risk Externship Program (Masters). Learn more about the career areas and lines of business at wellsfargojobs.com .
Program Overview | Are you aUNC Charlotte master's studentready to turn your data skills into real-world impact-without leaving the Queen City? Wells Fargo'sCorporate Risk Externship Programis your opportunity to dive into the world of financial risk, analytics, and AI while staying close to campus.
This paid, part-time externship is designed for students like you: curious, driven, and ready to explore how data science powers smarter decisions in banking. #earlycareers
What You'll Explore
You'll be matched with one of our high-impact risk teams:

• Model Risk Management (MRM):Ensure models are accurate and regulatory-ready.

• Independent Testing & Validation (IT&V): Validate the effectiveness of controls within the organization.

• Technology Risk Management:Use AI/ML to enhance risk oversight across all business lines.

• Risk Analytics, Data, and Reporting (RADAR): Deliver critical reporting, analytics, and business support solutions across the organization.

• Risk AI: Develop multi-agent solutions that support risk management across the company.

What You'll Experience:

• Code in Python, R, SAS, SQL, or Scala/Spark

• Develop AI tools and solutions that enhance risk management strategies

• Develop and validate models using statistical and machine learning techniques

• Collaborate with experts and present your insights to stakeholders

• Stay current with regulatory frameworks and risk trends

• Solve real problems with real data

Program dates:October 2026 - March 2027
Program Duration:20 hours a week
Program Location:Charlotte, NC
Required Qualifications:

• 6+ months of work experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Required Qualifications for Europe, Middle East & Africa only:

• Work experience, or equivalent demonstrated through one or a combination of the following: work experience, training, education

Desired qualifications:

• Enrolled in the Data Science or Computing and Informatics master's program at UNCC with an expected graduation date of May 2027 or later

• Completed undergraduate degree in Statistics, Computer Science, Economics/Econometrics, Operations Research, Computer Science, Engineering, or a related quantitative field

• Courses in model risk management, text mining and/or information retrieval highly preferred

• Experience and ability to demonstrate first-hand knowledge in several of these areas: data analytics, modeling, statistical inference, computing, big data analytics, Artificial Intelligence (machine learning, natural language processing, etc.)

• Knowledge of Programing skills and demonstrated ability to develop numerical algorithms in at least one of the following languages: Python, SAS, SQL, and Scala/Spark

• Strong verbal and written communication skills as well as interpersonal skills

• Ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment

• Ability to develop partnerships and collaborate with other business and functional areas

Applications openAugust 31-September 2, 2026 only!
Wells Fargo only considers candidates who are presently authorized to work for any employer in the United States and who do not require work visa sponsorship from Wells Fargo now or in the futurein order toretaintheir authorization to work in the United States.
Based on the volume of applications received, this job posting may be removed prior to the indicated close date. If you do not apply prior to the closing of thisposting, we encourage you to apply for other opportunities with Wells Fargo. Aftersubmittingyour application, pleasemonitoryour e-mail for future communications.
Posting End Date:
2 Sep 2026
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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.