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Salary
$55k – $79k per year (Estimated)
Location
In office (New York)
Seniority
Intern · 3+ years exp
Employment
Internship
Overview
Company
Impact
Profile match
American Express is a New York financial services company founded in 1850 as an express freight business that became a payments network and card issuer. Unlike the four-party networks it competes with, it issues most of its own cards and operates its own network, which lets it earn merchant discount revenue as well as interest and annual fees, and supports a premium rewards proposition built on travel and lounge access. Its business spans consumer and small business cards, corporate payments, merchant acquiring and travel services, and it is a component of the Dow Jones Industrial Average.

Business Unit/Role Specific Information

The Credit and Fraud Risk (CFR) team at American Express employs 3,500 global professionals focused on managing credit, fraud, and banking risk, optimizing risk trade-offs while delivering exceptional customer experiences. CFR’s work spans the entire customer lifecycle, supporting core processes like credit underwriting, fraud detection, servicing, and product development while also maintaining regulatory compliance and operational integrity. CFR leverages advanced analytics, data science, and AI/ML techniques to drive risk modeling, personalize decisions, and enhance customer experiences

How will you make an impact in this role?

The Data Science Intern will contribute to the development of predictive models and analytical solutions that inform key business decisions across credit, fraud, and marketing. By applying statistical, machine learning, and AI techniques to complex datasets, they will generate insights that enhance customer experience, strengthen risk management, and support innovation across the enterprise.

As an intern your responsibilities can include:

  • Independently lead an analytical project or workstream from problem definition through recommendation and final presentation.

  • Query, analyze, and derive insights from large and complex datasets using tools such as SQL, Hive, Python, and other analytical technologies.

  • Build, test, and evaluate predictive models using machine learning, statistical techniques, and advanced analytical methods.

  • Translate ambiguous business challenges into structured analytical approaches and actionable recommendations.

  • Leverage large-scale data assets and/or develop GenAI-enabled solutions to address business challenges and improve decision-making.

  • Partner directly with business stakeholders to understand objectives, align on solutions, and communicate key findings.

  • Develop and present recommendations that drive business outcomes, exercising independent judgment and accountability throughout project execution.

Minimum Qualifications:

  • Currently enrolled in a Graduate or PhD degree program with an expected graduation date between December 2027 and June 2028.

  • Pursuing a Master’s PhD degree program in Computer Science, Statistics, Data Science, Mathematics, Artificial Intelligence, or a related quantitative field.

  • 3+ years of professional experience in analytics, data science, quantitative research, machine learning, software engineering, or a related field.

  • Demonstrated ability to independently manage analytical projects and deliver results with limited direction.

  • Proficiency in Python and experience applying statistical, machine learning, or AI techniques to solve business or research problems.

  • Experience working with large datasets using SQL, Hive, or similar technologies and/or developing GenAI, NLP, LLM, or AI-powered solutions.

  • Strong analytical, communication, presentation, and problem-solving skills.

Preferred Qualifications

  • Experience presenting analytical insights and recommendations to stakeholders and influencing business decisions.

  • Published research, patents, academic publications, conference presentations, or other significant analytical project work.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.

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