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2027 Quantitative Analytics Program – Risk Analytics and Decision Science (RADS PhD) – Early Careers

Wells Fargo Bank


Job Location:

Charlotte, NC - USA

Monthly Salary: Not provided by the employer
Posted: 7 September 2026 (4 hours ago)
Application Deadline: 5 December 2026
Vacancies: 1 Vacancy

Job Summary

About this role:Wells Fargo is seeking talent to join the2027 Quantitative AnalyticsProgramRADS(PhD). Learn more aboutthecareerareas and lines of business at

Program Overview The Wells Fargo Quantitative Analytics Program offers PhD candidates an opportunity to apply advanced analytics artificial intelligence and machine learning to complex business challenges at one of the worlds leading financial institutions.

This 12-month development program combines hands-on project experience mentorship technical training and exposure to senior leaders. Through two six-month rotationsyoullwork alongside experienced quantitative professionals helping develop and evaluate innovative solutions that support business strategy risk management and customer experience across Wells Fargo.

Youllbeexpectedto bring fresh perspectives explore innovative approaches and contribute to solutions that support Wells Fargos strategic priorities. Along the wayyoulldevelop not only your technical capabilities but also the business acumen and leadership skills needed to succeed in a highly collaborative environment.

Upon completion of the programyoulltransition into a full-time role aligned with your skills interests programexperienceand businessneeds.#earlycareers

You could work on high-impact projects like:

  • Forecasting loss and revenue for credit card loan portfolios

  • Developing credit scorecards for consumer decisioning strategies

  • Building models toidentifymoney laundering patterns across massive transaction databases

  • Predicting operational losses using statistical and machine learning modeling

  • Applying statistical and quantitative techniques tovalidatemodel design calibration and implementation.

WhatYoullExperience:

Step into a data-driven environment where advanced analytics machine learning and emerging technologies power smarter decisions across the the Quantitative Analytics Programyoullwork at the intersection of data risk andinnovationsolving complex problems that directlyimpactcustomers and the broader financial system.

Youll design and deploy models that inform critical decisions across credit risk financial crime customer experience and operations. From forecasting portfolio performance to applying generative AI in underwriting and customer interactions your work will drive meaningful outcomes at scale.

Working with large real-world datasetsyoullpartner with cross-functional teams and senior leaders to turn sophisticated quantitative techniques into actionable insights. Whether detecting fraudoptimizingstrategies or building AI-driven solutionsyoullplay a key role in shaping how data powers the future of banking.

Program dates:July 2027 - July 2028

Program Duration:12 months

Program Location:Charlotte NC


Required Qualifications:

  • 2 years of Quantitative Analytics experience or equivalent demonstrated through one or a combination of the following: work experience training military experience education
  • Masters degree or higher in statistics mathematics physics engineering computer science economics or quantitative discipline


Required Qualifications for Europe Middle East & Africa only:

  • Experience in Quantitative Analytics or equivalent demonstrated through one or a combination of the following: work experience training education
  • Masters degree or higher in statistics mathematics physics engineering computer science economics or quantitative discipline

Desired Qualifications:

  • Currently pursuing a PhD degree with an expected graduation date between December 2026 June 2027ORgraduatedfrom a PhD program after May 2024 andarecurrently completing a postdoc withemphasis inStatistics Data Science Mathematics Econometrics Computer ScienceEngineeringor related quantitative field.

  • Excellent programing skills and use of statistical software packages such as Python R SQLSparkand Java

  • Strong quantitative and analytical skills with the ability to apply data analysis modeling visualization statistics research and generative AI to generate insights adapt quickly and support innovative solutions.

  • Ability to execute with urgency apply data and software engineering skills to design develop and deliver scalable solutions and drive operational excellence with strong data management and an enterprise mindset.

  • Strong communicationskills with the ability to foster an inclusive environment and activelyseek 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.

  • Experience anddemonstratedfirst-hand knowledge in a number of these areas: machine learning/AI models data analysis statistical modeling data management and computing

Join us at Wells Fargo and become a part of a dynamic team that is shaping the future of the financial industry. Apply now and embark on a journey towards personal and professional growth in quantitative analytics.

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:

    20 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 units 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 visitDisability 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.


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