American Express Careers

Manager - Customer Marketing Decision Science

Gurgaon, India
Operations Risk Management

Apply Get Referred

Job Description

American Express is a global services company and the world’s largest card issuer. Our direct relationships with many millions of consumers, businesses and merchants worldwide - combined with our leading edge marketing, information management and rewards capabilities - enable us to offer an array of valuable services that enrich lives, build business success, encourage financial responsibility and create communities of people with common interests.

American Express for 11th consecutive year has been voted among India’s top 10 workplaces by the Great Place to Work institute. In recognition of our consistent performance, we were nominated to the Great Place to Work “Hall of Fame”.

At American Express, we serve customers, not transactions. We’re widely known for providing superior customer service and have been recognized for a number of achievements including being ranked highest in customer satisfaction within the credit card industry by J.D. Power for seven consecutive years.

A career at American Express is rich in experience and offers opportunities to build lasting relationships with our customers.

Come join us and realize your potential.

American Express is one of the world's largest, most analytically sophisticated financial services providers. The American Express Brand stands for unsurpassed customer service and expertise in quantitative analysis is central to our success in serving customers and delivering for shareholders. The large team of econometricians and programmers thrives in a culture where problems are solved with innovative approaches and precise analysis. Customer marketing vision is to deliver the most relevant content to the right customer at the right time through their preferred channel(s) of choice.

The Customer Marketing Decision Science – Merchant Recommender & Feature engineering team within the Enterprise Digital & Analytics (EDA) organization is responsible for developing merchant recommender solutions as well as all global feature development and signal processing including Commerce Graph. In particular, the team will lead and provide the support for development of world-class personalization capabilities catering to all global markets. This would involve development & deployment of cutting edge Machine Learning / Data Science solutions which will be able to drive industry leading performance lifts. This will in turn require the candidate to exhibit a high level of expertise in data understanding through statistical analysis, decision support logic and data techniques. Within this group, we are looking for a band 35 Manager who would be presented with an exciting opportunity to step into a very challenging role. He / She will drive improvements in generating data driven actionable strategies to enable business growth initiatives. The incumbent will be in charge of a team and be responsible for appraisal, mentoring and reviewing the work done by the team. Key focus areas will include:

• Devising, Designing & Developing cutting edge, customized Machine Learning Algorithms
• Leverage the power of closed loop through Amex network to make offer targeting more intelligent and relevant
• Innovation with focus on developing newer and better approaches using big data & machine learning solution
The successful candidate is expected to stay current in their field and up to date with the latest data science, machine learning, business statistics, algorithms and data mining practices. Should also have an understanding and passion for trends in digital marketing, social, location and mobile based marketing efforts.


• Master's Degree In Economics, Statistics, Quantitative Analysis/M Tech/ MBA With Quantitative Specialization and 3.5+ years of analytical/econometric experience.
• Knowledge and experience of statistical and analytical techniques is preferred. Competency in standard data mining and advanced deep learning techniques is also desirable e.g. Decision trees and Neural Networks
• Exposure to analysis / modeling of digital data is a plus.
• Practical coding experience with statistical analysis programming languages such as SQL, HIVE, Python and Pyspark. Knowledge/Exposure to Big data is again a plus.
• Prior experience in mentoring and guiding junior members in the team.

ReqID: 18012019
Schedule (Full-Time/Part-Time): Full-time
Apply Get Referred