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Manager - Information Management, Acquisition Analytics & Data Science
The ‘Global Commercial Prospect Acquisition Analytics and Data Science’ team is part of the Global Information management group within American Express. This group is responsible for targeting and acquiring customers over online and offline channels and delivering world-class Analytics, Insights and Data Products for the Global Corporate Payments portfolios.
You will be challenged with designing and creating world class prospect marketing analytics by leveraging machine learning and other advanced methodologies. The person will perform data analysis, modeling, synthesize conclusions, communicate and present recommendations to partners. The position is part of a highly collaborative environment, interacting with and influencing partners across the Global Commercial Payment business at American Express
Responsibilities will include:
- Creating world class analytics, developing cutting edge commercial capabilities and adding valuable insights to improve models
- Enable transformation in decision making capabilities across channels by exploring big data/machine learning techniques such as Random Forest, Gradient Boosting Machines, k-nearest neighbour, support vector machines and Text Mining/NLP. Intelligently integrating traditional structured data with unstructured data
- Creating data segmentation & optimization strategies for targeting profitable prospects with the right product/incentive across multiple channels
- Quantitatively determining value and deriving insights, then assuring the insights are leveraged to create positive impact to decision science models and early warning signals.
- Develop insights into customer behaviour and introduce new approaches to transform complex behavioural data into actionable information
As the successful individual in this position you will have:
- A Master's Degree in a quantitative field (e.g. Finance, Engineering, Physics, Mathematics, Computer Science or Economics) or PhD.
- Strong programming skills are required. Experience with BIG DATA PROGRAMMING LANGUAGES (HIVE, PIG), PYTHON, JAVA, R. Expertise or ability to pick up strong SAS / SQL skills
- Solid technical and analytical skills with the ability to apply both quantitative methods and business skills to create insights and drive results
- Strong knowledge of data mining techniques, including regression analysis, clustering, decision trees, neural networks, SVM (support vector machines)
- Demonstrated ability to work independently and across a matrix organization partnering with capabilities, decision sciences, technology teams and external vendors to deliver solutions at top speed
- Knowledge of reviewing company financials and commercial bureau data is preferred
Schedule (Full-Time/Part-Time): Full-time