Responsibilities include:

• Leverage quantitative skills to provide decision support to business teams on Enterprise-wide forecasting for AR/ ADB and FCR, including, but not limited to, model ownership and results analyses
• Propose and implement solutions to ad-hoc business problems independently, leveraging data and insights to play the role of strategic advisors
• Lead Planning activities including Risks & Opportunities (R&O), Long-Range Plan (LRP) and Annual Plan as it relates to AXP AR, ADB, FCR and Total Interest Income
• Deepen trust-based relationships with a variety of stakeholders and levels across the Enterprise, including, but not limited to EFP&A, BU FP&A, LFO teams and business partners
• Lead multiple volumes-related initiatives concurrently while adhering to deadlines
• Assist in developing/enhancing/automating Lend predictive modeling that incorporates card member behaviors and increased level of data granularity
• Use machine learning techniques to improve forecasts and produce business insights; leverage visualization and reporting tools
• Provide thought leadership into key findings and actionable recommendations to influence business strategy
• Understand and adopt emerging technology that can affect the application of the quantitative analytical approaches and technique to solve business problems
• Perform financial planning and analysis that serve as the basis for key internal and external communications.
• Ensure the flow of accurate and complete financial information by liaising between internal and external reporting and broader finance organization.
• Support forecast model risk management process by working with risk team on model monitoring, interpretability, and parameter tuning.
  
  

Minimum Qualifications:

• Solid understanding of card economics
• Highly motivated individual with desire to work on ambiguous projects; With the ability to break down and execute on complex ideas
• Ability to solve ad hoc business problems independently and manage multiple priorities and projects while adhering to deadlines
• Master’s degree in a quantitative field
• Proficiency in SQL, Hive, Python, Pyspark, Machine Learning Techniques

Preferred Qualifications:

• 5-10 years of experience preferred
• Python/R skills strongly preferred
• Statistical/Predictive modeling knowledge and experience strongly preferred
• Experience with data visualization tools preferred
• Strong analytical, organizational, and problem-solving skills with good attention to detail

·       Bachelors/Masters or PhD in a quantitative field - Applied Mathematics, Physics, Engineering, Computer Science, Economics

• Strong desire and ability to learn

Skills:

• Highly motivated individual with desire to work on ambiguous projects, with the ability to break down and execute on complex ideas.
• Be data-driven, outcome-focused and fast learner.
• Strong analytical, organizational, and problem-solving skills with good attention to detail
• Ability to influence people across all levels of the organization.
• Ability to explain complex mathematical concepts.

Ability to solve ad-hoc business problems independently and manage multiple priorities and projects while adhering to deadlines.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

• Competitive base salaries 
• Bonus incentives 
• Support for financial-well-being and retirement 
• Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) 
• Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need 
• Generous paid parental leave policies (depending on your location) 
• Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) 
• Free and confidential counseling support through our Healthy Minds program 
• Career development and training opportunities

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.