American Express Careers
Director, Commercial Data Quality & Data Products Analytics
Director – Commercial Data Quality & Data Products Analytics, Enterprise Digital & Analytics (ED&A)
The ‘Commercial Data Quality & Data Products Analytics’ Team is part of the Global Commercial and Merchant Analytics (GCMA) Team in Enterprise Digital and Analytics group within American Express.
GCMA is responsible for targeting, acquiring, engaging and retaining commercial customers over online and offline channels and delivering world-class analytics, insights and data products for the Global Commercial Services (GCS) and Global Merchant Services (GMS). In this role, you will be challenged with designing and creating world class data products and marketing analytics by leveraging best in class data science techniques. The person will also be responsible for partnering with colleagues with GCMA and across sales and marketing partners to use the data products for driving business outcomes.
- Define, Design, Create, and Implement data science & analytical solutions on data products and data quality of commercial data across prospects & customers including US and International markets
- Collaborate with Decision Science and Capabilities to manage, guide and build analytical solutions to improve coverage & accuracy of data including activities such as identification, arbitration, modeling , implementation and execution into business outcomes
- Explore the usage and implementation of latest big data/machine learning techniques and intelligently integrating traditional structured data with unstructured data to drive profitable growth in commercial acquisition and charge volume.
- Introduce new approaches to transform complex customer behavioral data into data products that serve the entire Global Commercial organization.
- Continually broaden and strengthen knowledge of analytical methods and tools.
- Master's Degree or MBA, in a quantitative field (e.g. Finance, Engineering, Physics, Mathematics, Computer Science or Economics)
- Strong programming skills (C, C++, JAVA, Python, R etc.)
- Familiarity with recommendation systems such as collaborative filtering, k-nearest neighbors, association rules, market basket analysis, SVD (singular value decomposition), and matrix factorization methods
- Experience working with very large datasets using Big Data tools and platforms (Hadoop, PIG/HIVE/Mahout)
- Strong working knowledge of data mining techniques, including regression analysis, clustering, decision trees, neural networks, SVM (support vector machines)
- Demonstrated ability to apply cutting edge statistical techniques to business problems and to leverage external thinking (from academia and/or other industries)
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 position
Schedule (Full-Time/Part-Time): Full-time