American Express Careers
Manager - GMS Fraud Risk Decision Sciences
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.
Don’t live life without it.
The CFR team helps drive profitable business growth by reducing the risk of fraud and maintaining our customers' confidence in the security of our products. It utilizes an array of tools and ever-evolving technology to detect and combat fraud, minimize the disruption of good spending and provide a world-class customer experience. The team leads efforts that leverages data and digital advancements to improve service and risk management as well as enable commerce and drive innovation. CFR is responsible for developing and monitoring statistical models for predicting individual and commercial behaviors such as credit risk, fraud risk, spending and revolve. These models are used for key business decision made across the customer life cycle to manage risk and accelerate profitable business growth. Underpinning our growth as a company are the tools and capabilities that ensure we prudently take and mange risk a viable way.
The successful candidate will be a member of Global Fraud Decision Science team and will lead a team of analysts focused on leading decision science efforts for mitigating fraud for Global Merchant and Network Services.
Purpose of the Role:
Develop and enhance existing American Express statistical models by leveraging best-in-class modeling techniques and data across various stages of card member life cycle.
Specific responsibilities include:
• Develop and enhance existing models by utilizing the best-in-class modeling techniques
• Evaluate new data sources – internal and external, as well as new variables designed from extensive case reviews for their efficacy in the models
• Be well versed in the model governance processes
• Work closely with members of the strategy teams located in multiple geographies to ensure seamless implementation
Business Outcome - Ensure modeling accuracy and enhance modeling efficiency in existing processes using Machine Learning & Innovate modeling techniques and variable creation
• 4+ years of experience in building and implementing machine learning models in a corporate setting
• Strong analytical and project management skills and ability to prioritize and manage multiple initiatives simultaneously
• Winning attitude that motivates and develops people
4+ years with relevant experience in analytical/ modeling skills
Post Graduate in Statistics/Mathematics/ Economics/ Engineering/ Management
-Put enterprise thinking first, connect the role’s agenda to enterprise priorities and balance the needs of customers, partners, colleagues & shareholders.
- Lead with an external perspective, challenge status quo and bring continuous innovation to our existing offerings
- Demonstrate learning agility, make decisions quickly and with the highest level of integrity
- Lead with a digital mindset and deliver the world’s best customer experiences every day
Working knowledge of Gradient boosting machine algorithm
Advanced statistical techniques
R, Python, C, C++, Java, SAS, SQL
Experience with various supervised and unsupervised techniques preferred
Knowledge of Platforms:
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Mar 15, 2019, 1:40:08 AM