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Data Scientist

American Express
Data Scientist
New York, US
90,000 - 165,000
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Job Description

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

As a brand built on going above and beyond to provide the best customer experience, having the most exceptional colleagues is paramount. As the face of the company, you can create positive interactions with our customers every day–from curating a unique travel or lifestyle experience to helping them with their everyday needs. And you can grow your skills through industry-leading training and ongoing coaching, all while learning what it means to continually set the standard for world class, customer-first service.

Decision 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 best practices when it comes to developing the analyses, models, and algorithms that power our customers’ digital experiences.

This critical team is responsible for managing 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.

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.

The role will entail some of the below listed responsibilities:

  • Work with massive amounts of digital data (Web, App, API) and sophisticated tools in an industry leading Big Data environment. 
  • Build NLP driven solutions from identifying business problems, to collecting training dataset, to analyzing data, to modeling, to validating and to delivering NLP models
  • Build everything from basic reports to advanced machine learning models and algos to drive improvements to our customer’s online and mobile app experiences.
  • Work with product owners to revolutionize the product and content design with a data-driven approach
  • Collaborate with tech partners to test, implement and deploy modeling solutions to production system.
  • Develop insights into customer behavior and introduce new approaches to transform complex behavioral data into actionable information
  • Leverage 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


  • Masters/PhDs in a quantitative field (Computer Science, Statistics, Mathematics, Physics, Operation Research and etc.) with hands-on experience leveraging sophisticated analytical and machine learning techniques. PhD degree with practical experiences NLP is a significant plus.
  • Expertise in an analytical language (Python, R or the equivalent), and experience with databases (Hive, SQL, or the equivalent). Knowledge of SAS is a plus but not required.
  • Deep understanding of machine learning/statistical algorithms such as deep learning and boosting. Experience with data visualization is a plus
  • Demonstrated ability to frame business problems into mathematical programming problems, leverage external thinking and tools (from academia and/or other industries) to engineer a solution and deliver business insights.
  • Ability to work effectively in a team environment
  • Independent thinker who’s organized, has great attention to detail, and can multi-task
  • Strong communication skills
  • Ability to learn quickly and work independently with sophisticated, unstructured initiatives
  • Ability to integrate with cross-functional business partners worldwide
  • Proficient in presentation tools, including Excel and PowerPoint
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