Manager, Data Analytics
American ExpressLead analytics, performance management, and portfolio strategy for American Express commercial client management. Advise senior leaders on growth, forecasting, and data-informed decisions.
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American Express is a global financial services company operating across banking, finance, and B2B payments. Its business includes consumer, business, and corporate credit cards; payment and merchant services; savings accounts, certificates of deposit, and personal loans; as well as rewards, travel programs, corporate payment solutions, financial education, security services, and cardmember and merchant support.
Senior Data Science Analyst
Build predictive models that inform American Express decisions across risk, fraud, and marketing. Analyze large datasets to uncover business insights and support profitable customer outcomes.
Description
- Build, deploy, and validate predictive models.
- Apply models within economic frameworks to support profitable decisions in risk, fraud, and marketing.
- Learn how American Express operates and what factors shape its business decisions.
- Analyze large datasets to uncover business insights and develop innovative solutions.
- Use the American Express network to make decisions more informed and relevant.
- Create improved approaches using big data and machine learning.
- Present and organize findings across prospect and customer domains for leaders and key partners.
- Track developments in finance, payments, and analytics.
Requirements
- MBA or a master’s degree in economics, statistics, computer science, or a related field.
- 24–48 months of experience in analytics or big data workstreams.
- Work effectively as part of a team.
- Drive project deliverables toward business results.
- Strong communication and interpersonal abilities.
- Solve problems creatively, learn quickly, and work independently on complex, unstructured initiatives.
- Collaborate with cross-functional business partners around the world.
- Experience with SAS, R, Python, Hive, Spark, and SQL.
- Knowledge of supervised and unsupervised methods, including active and transfer learning, neural models, decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, MapReduce, and feature engineering.
- Employment is contingent on successfully completing a background verification check, subject to applicable laws and regulations.
Benefits
- Competitive base salary.
- Bonus incentives.
- Support for financial well-being and retirement.
- Medical, dental, vision, life insurance, and disability coverage, depending on location.
- Flexible hybrid, onsite, or virtual work arrangements, depending on role and business needs.
- Generous paid parental leave, depending on location.
- Complimentary access to global onsite wellness centers staffed by nurses and doctors, depending on location.
- Free, confidential counseling through the Healthy Minds program.
- Career development and training opportunities.
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