Data Science and Analytics Manager – Global Rewards Finance

Key Skills

Java Programming, Leadership, Finance, Management, Python Programming, SQL, Machine learning techniques, Data science techniques, Data Modeling, Statistics, PySpark, SAS, Large data sets

Job Description

At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way. When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day.

The Global Rewards Finance team manages one of American Express’s largest balance sheet items – the reserve for Membership Rewards in the US and over twenty international markets. The team also provides strategic and financial analysis to help develop winning strategies that enhance customer experience, increase engagement, and help to grow our business.

The ideal candidate will bring a unique balance of technical skills combined with a strategic mindset and the ability to communicate effectively. He or she will be part of the Data Science and Analytics team, made up of highly-talented individuals whose primary remit involves synthesizing data, building predictive models, and conducting advanced analytics to drive actionable business recommendations.

This is an excellent opportunity for individual to work with a number of internal and external agencies and business partners including, but not limited to, Product Management, Controllership, Model Validation, Audit, and Technology. This is a high-visibility role with a focus on building innovative solutions and developing global rewards strategies while maintaining effective governance and controls over a multi-billion dollar line item.

Responsibilities

• Build and enhance predictive models including the Ultimate Redemption Rate model, improving forecast accuracy as well as stable and explainable model outcomes
• Migrate current production codes from SAS to Python
• Develop and maintain strong relationships with internal and external agencies including Controllership, Model Validation, Audit and others to satisfy requests and enhance models as needed
• Own the financial analysis for rewards initiatives, leverage analytical and data mining techniques to optimize loyalty programs across businesses in US and international markets and across lines of business
• Communicate verbally and in writing to various stakeholders to educate them about data-driven insights and recommendations
• Evaluate current processes and provide improvement/efficiency recommendations

Skills and Qualifications:

• Minimum 2 years of work experience
• Advanced degree in Statistics, Data Science, Economics or Computer Science
• Experience in statistical/predictive modeling and experience with machine learning is a plus
• Experience with SAS, SQL, Python, Pyspark
• Ability to write a production level code in Python
• Strong analytical skills, quantitatively oriented, and comfortable working with large sets of data
• Demonstrated experience with data manipulation techniques
• Thought leadership and creativity in solving challenging, and potentially ambiguous, business problems
• Excellent verbal and written communication skills with the ability to effectively disseminate information to audience with various levels of technical knowledge
• Ability to build relationships with cross-functional teams by influencing with sound logic

Why American Express

Talk to our people and you’ll find out what we’re all about. Open, creative, risk-taking, collaborative and innovative are just some of the expressions you’ll hear. It’s our culture that makes American Express an outstanding place to work, and a big part of why we regularly win best workplace awards all over the world. If you’re ready to take on a challenge and make an impact, you owe it to yourself to launch or grow your career here.