Manager-Marketing Analytics & Data Science

Job description

This position is in the Integrated Marketing Solutions – US Customer Marketing Analytics and Data Science team and is responsible for expanding and deepening relationships with customers and maximizing profitability for American Express through best-in-class analytics and data science.

In this team, you will have the opportunity to provide critical analytics that drive the core business strategy for inbound channels as well as outbound marketing at American Express. You will perform strategic analyses to identify business opportunities, model customer behaviors to effectively target customers, and perform in-market test & learn to understand the effectiveness of key marketing initiatives throughout the customer lifecycle.

Key responsibilities would be to:
· Develop strong relationship with internal marketing partners to understand and help frame key business problems
· Build and explore customer datasets to provide context on the business problems being addressed
· Conduct strategic analyses to inform business decisions and provide actionable recommendations. Write and present fact based presentations to key stakeholders
· Manage BAU campaign targeting, experimental design, results read, etc. across the entire US consumer portfolio

Desired profile

·  Advanced degree in a statistics/business/economics/decision science related field with 3+ years of work experience leveraging analytics and data science to drive business results
·  Experience manipulating and extracting business/customer insights from extremely large, complex datasets
·  Strong analytical skills, intellectual curiosity, and an innovative approach to solving business problems
·  Strong programming skills are required (SQL, SAS, R, PYTHON, HIVE, etc.)
·  Self-motivated and ability to work autonomously on multiple projects simultaneously
·  Strong communications and relationship building skills with an ability to develop and deliver effective presentations
·  Strong technical background with experience in experimental design, predictive modeling, segmentation, etc.