Campus Graduate - 2025 Credit & Fraud Risk, Decision Science Summer Internship New York, NY
You Lead the Way. We’ve Got Your Back.
With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.
At American Express, you’ll be recognized for your contributions, leadership, and impact-every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.
Join Team Amex and let's lead the way together.
Business Unit/Role Specific Info
As a Data Science colleague, you have the opportunity to make your mark on technology and life at American Express. You’ll be challenged everyday as we work together to create digital products and develop actionable data-driven insights to meet the customers of tomorrow. It is an exciting opportunity for someone who wants to help shape digital experiences for one of the world’s top brands.
Where are these roles located within American Express?
Global Decision Science : Data Science colleagues will serve as a key member of the Credit and Fraud Risk organization. We seek a thought-leader and a problem-solver who can blend business, technical, and industry standard processes when it comes to developing the analyses, models, and algorithms that power our customers’ digital experiences.
This vital team is responsible for leading enterprise risks throughout the customer lifecycle, across our consumer and commercial businesses, and across all our global products. We develop industry-first data capabilities, build profitable decision-making frameworks, create machine learning-powered predictive models, and improve customer servicing strategies.
How Will You Make an Impact in This Role?
Our Decision Science teams use industry leading modeling and AI practices to predict customer behavior. We develop, deploy and validate predictive models and support the use of models in economic logic to enable profitable decisions across credit, fraud, marketing and servicing optimization engines.
What type of work can you expect to do in Data Science at American Express?
The specific job responsibilities would depend on the team you are selected in for a summer internship role. Broadly the role could entail some of the below listed responsibilities:
Work with extensive amounts of digital data (Web, App, API) and sophisticated tools in an industry leading Big Data environment.
Build everything from basic reports to advanced machine learning models and algos to drive improvements to our customer’s online and mobile app experiences.
Develop insights into customer behavior and introduce new directions to transform complex behavioral data into useful information
Bring to bear the power of closed loop through Amex network to make decisions more intelligent and relevant
Innovate with a focus on developing newer and better approaches using big data & machine learning solutions
Minimum Qualifications
Currently enrolled in a full-time Masters/PhD degree program in a quantitative field (Computer Science, Statistics, Mathematics, Physics, Operation Research and etc. ) with hands-on experience using sophisticated analytical and machine learning techniques. PhD degree with practical experiences NLP is a significant plus.
Students must have a graduation date between December 2025 and June 2026
Preferred Qualifications
Passion for improving end-to-end customer experience, innovation and customer first thinking
Proven track record to frame business problems into mathematical programming problems to engineer a solution and deliver business insights
Expertise in an analytical language (Python, R or the equivalent), and experience with databases (Hive, SQL, or the equivalent)
Ambitious thinker who’s organized, has excellent attention to detail, and can multi-task
Ability to blend big picture thinking with fine details and lead many stakeholders
Willing to try new things, experiment, and share fresh perspectives
Proficient in presentation tools, including Excel and PowerPoint
Excellent written and verbal communication skills
Our team will review completed applications on a rolling basis. We appreciate your patience while we consider your application and will be in contact with you.
Salary Range: $38.45 to $87.00 hourly + sign-on bonus
The above 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.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions
We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life.
Benefits include:
For a full list of Team Amex benefits, visit our 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.
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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