Become part of the digital transformation and help revolutionize the financial services industry.
At American Express, we provide customers with access to products, insights and experiences that enrich lives and build business success. Our customers include our Cardmembers as well as the small businesses, merchants, corporations, and bank partners that are all members of the dynamic American Express network.
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?
Data Science colleagues will serve as a key member of teams in the Credit and Fraud Risk and Enterprise Digital & Analytics organizations. We seek a thought-leader and a problem-solver who can blend business, technical, and industry best practices – sweating every fine detail when it comes to developing the analyses, models, and algorithms that power our customer’s digital experiences.
Enterprise & Digital Analytics:
An exciting opportunity for someone who wants to help shape, refine and build, Prospect and Customer digital connections, experiences and interactions for one of the world’s most respected companies, through advanced statistical techniques, AI, and machine learning. Enterprise Digital and Analytics team charter is to be an engine of growth, marketplace differentiation and efficiency for American Express.
Big Data Labs:
Develop Big Data capabilities, tools and techniques to enhance Credit and Fraud Risk, and Information Management functions.
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
Decision Science roles in these teams:
Our Decision Science teams use industry leading modeling and AI practices to predict customer behavior. Development, deployment and validation of predictive model(s) and supporting use of models in economic logic to enable profitable decisions across risk, fraud and marketing.
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 full-time role. Broadly the role could entail some of the below listed responsibilities:
- 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 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
We have the know-how, creative platform and global reach to make nearly any idea a reality. Do these describe you?
- Passion for improving end-to-end customer experience, innovation and customer first thinking
- Strong interest in analytics and data mining space and ability to collaborate with technology and product partners
- Independent thinker who’s organized, has great attention to detail, and can multi-task
- Ability to blend big picture thinking with fine details and manage many stakeholders
- Strong analytical, problem-solving/quantitative skills
- Willing to take risks, experiment, and share fresh perspectives
- Proficient in presentation tools, including Excel and PowerPoint
- Excellent written and verbal communication skills
Ability to handle large datasets using SAS, SQL, R, Python or another similar programming language
- Advanced Degree (i.e. MS or PhD) in a quantitative field such as Economics, Statistics, Mathematics, Operations Research, Engineering, Computer Science
- Currently enrolled in full-time Graduate degree or PhD program - Students must have a graduation date between December 2020 and June 2021
- Candidates with relevant industry experience of 1-5 years can also apply
Why American Express?
There’s a difference between having a job and making a difference.
American Express has been making a difference in people’s lives for over 160 years, backing them in moments big and small, granting access, tools, and resources to take on their biggest challenges and reap the greatest rewards.
We’ve also made a difference in the lives of our people, providing a culture of learning and collaboration, and helping them with what they need to succeed and thrive. We have their backs as they grow their skills, conquer new challenges, or even take time to spend with their family or community. And when they’re ready to take on a new career path, we’re right there with them, giving them the guidance and momentum into the best future they envision.
Because we believe that the best way to back our customers is to back our people.
The powerful backing of American Express.
Don’t make a difference without it.
Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability status, or any other status protected by law.
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Schedule (Full-Time/Part-Time): Full-time
Date Posted: Sep 15, 2020, 6:16:44 AM
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.