Analyst - Data Science

American Express

American Express offers an exciting career opportunity within their Credit & Fraud Risk Finance team, renowned for delivering impactful credit-risk insights and forecasts. The Analyst position focuses on using the latest data tools and techniques to support strategic corporate planning. The company values integrity and a diverse work environment where every team member's contribution is recognized and rewarded.

In this role you can expect to have the responsibilities:

• Develop and maintain econometric models for US and international portfolios.
• Analyze market trends and identify performance drivers.
• Update model documentation for validation and regulatory submission.
• Support stress testing exercises across American Express.
• Present statistical modeling techniques to various internal and external stakeholders.
• Collaborate with cross-functional teams like Treasury and Corporate Planning.

This role comes with the following benefits:

• Competitive base salaries with bonus incentives.
• 6% Company match on retirement savings plan.
• Comprehensive medical, dental, vision, life insurance, and disability benefits.
• Flexible working model: hybrid, onsite, or virtual.
• 20+ weeks of paid parental leave.
• Free access to global on-site wellness centers.
• Confidential counseling support via Healthy Minds program.
• Career development and training opportunities.

This role requires you to have:

• Degree in mathematics, computing, or statistics.
• Strong understanding of statistical/predictive models and data analysis.
• Proficiency in Python and SQL for large data manipulation.

You would benefit from having:

• 1-2 years of relevant experience.
• Experience with machine learning algorithms such as Regression and Gradient Boosting.
• Ability to communicate complex ideas clearly.
• Curiosity and analytical skills to define and explore inquiries.

American Express is committed to being an equal opportunity employer, ensuring a discrimination-free work environment. They support flexible work arrangements to balance professional and personal life needs.