Campus Graduate II Summer Internship Program - 2027 Global Decision Science, Credit & Fraud Risk - New York, NY

Job Description

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

Responsibilities

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.

Qualifications

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.

About us

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

About

We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:

• Competitive base salaries
• Flexible work arrangements and schedules with hybrid and virtual options with Amex Flex
• Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
• Free and confidential counselling support through our Healthy Minds program
• Career development and training opportunities

For a full list of Team Amex benefits, visit out Colleague Benefits Site.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
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The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.​