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Campus Graduate - 2022 Finance Data Science Summer Internship

About AMEX
At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible— and we’re proud to back each other every step of the way.
Join #TeamAmex and let’s lead the way together.
Our industry is rapidly evolving, and we need courageous, quick thinkers who can shape the strategic decisions that lead our business forward. Whether it’s negotiating with some of our largest global partners or creating next year’s financial plan, you can influence both our day-to-day P&L and the future direction of the Company. As part of the team, you can have the opportunity to learn and use the latest data tools and technologies and explore a range of roles to grow your career.

Business Unit/Role Specific Info
At American Express, we leverage Machine Learning and Artificial Intelligence to make smarter predictions and provide actionable insights. We empower colleagues to unlock potential through Data, Technology & Innovation. Our team’s goal is to help the organization make fact-based and scientifically developed decisions around risk and opportunities.
Finance Decision Scientists work closely with other teams in Finance, Business and Risk to define new methods of prediction and align them with business strategy. This position will be part of a highly talented team with strong intellectual curiosity. Our team is excited about solving business problems through data and technology.
Team’s Responsibilities include:
  • We innovate and develop new and more sophisticated ways to predict top line metrics for our business. These predictions inform both short-term and long-term strategy for senior management.
  • We develop models and strategic insights to help deliver increasing value to our card members, while managing one of the largest balance sheet items at American Express.
  • We develop advanced models and analytical tools used to influence the company's decisions related to credit, fraud, and recessionary preparedness.
  • We manage and fund the overall balance sheet of the company by focusing on efficient asset-liability management, liquidity risk management and capital adequacy. 
  • Hands-on experience managing/leading projects using large amounts of data and application of advanced predictive analytics
  • Proficiency in SQL and any of the following programming languages: Python, SAS, or R
  • Machine learning development experience is strongly preferred
  • Tableau or other visualization tools experience
  • Highly motivated individual with desire to work on ambiguous projects, with the ability to break down and execute on complex ideas
  • Be data-driven, outcome-focused and a fast learner
  • Strong analytical, organizational, and problem-solving skills with strong attention to detail
  • Ability to explain complex mathematical concepts
  • Ability to solve ad-hoc business problems independently and projects while adhering to deadlines
  • Currently enrolled in a full-time Undegraduate or Graduate degree program in Applied Mathematics, Physics, Engineering, Computer Science, Statistics, Quantitative Finance
  • Students must have a graduation date between December 2022 to June 2023
For more information, please visit our career website at
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 by April 30th.
Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions.
Click here to view the "EEO is the Law" poster and supplement and the Pay Transparency Policy Statement.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, age, or any other status protected by law.