Analyst- Data Analytics

Job Title: Financial Crime Risk Data Analyst

Company: American Express
Location: Hybrid (Work from home and office)

About American Express:

At American Express, we believe in the power of people and businesses to progress in incredible ways. As a global company, we’re committed to supporting our customers, communities, and colleagues. When you join Team Amex, you’ll be part of a diverse, inclusive community with an unwavering commitment to providing the world’s best customer experience—every day. We offer a supportive environment where everyone has the opportunity to share in the company’s success and grow their career.

Team Overview:

The International Operational Excellence team at American Express is a newly expanded organization responsible for supporting our international Issuing and Acquiring businesses. We ensure a robust first line of defense, support business growth objectives, and manage risk, respond to new regulations, and develop new products across 27+ markets.

Our Financial Crime Risk Data Integrity team leverages data analytics to drive Anti-Money Laundering (AML) solutions. We’re committed to transforming strategies and using data to fight financial crime while maintaining an effective control framework. As part of this team, you’ll help develop data-driven strategies to optimize AML risk and enhance customer experience.

Job Overview:

As a Financial Crime Risk Data Analyst, you will perform advanced analytics to support Financial Crime Risk (FCR) initiatives in a dynamic regulatory environment. Your role will focus on working with large datasets, monitoring KYC/KYB health, and driving insights that optimize AML risk. You'll partner with cross-functional teams including Compliance, Technology, and PMO, and use tools like SQL, Python, and Tableau/Sisense to define and implement effective AML risk strategies.

Responsibilities:

• Perform analytics to support multiple workstreams within FCR (Financial Crime Risk) using SQL and Python.
• Analyze large volumes of structured and unstructured data to drive meaningful insights and actionable recommendations.
• Create and maintain dashboards in tools like Tableau and Sisense to monitor KYC/KYB health of Cardmembers and Legal Entity portfolios.
• Define and build data-driven strategies to optimize AML risk and enhance customer experience.
• Partner with Compliance, Technology, and PMO teams to define and understand AML risk strategies and regulatory requirements across markets.
• Collaborate with cross-functional teams to ensure the effective implementation of AML solutions.

Qualifications:

• Education: Degree in a quantitative field such as Finance, Statistics, Economics, Mathematics, or Engineering.
• Experience: 2+ years of relevant work experience in financial crime risk, data analysis, or related areas.
• Skills:
  • Strong analytical and problem-solving skills, with the ability to handle unstructured data.
  • Proactive mindset with the ability to collaborate and thrive in a fast-paced, results-driven environment.
  • Experience with SQL, Hive, Python, and R for data analysis and reporting.
  • Ability to translate complex data insights into clear, actionable strategies for both technical and non-technical stakeholders.
  • Strong communication skills with attention to detail.
  • Knowledge of credit risk strategy or the payments industry is a plus.

Benefits:

American Express provides comprehensive benefits to support the holistic well-being of our colleagues, including:

• Competitive base salary and bonus incentives.
• Comprehensive medical, dental, and vision insurance, along with life and disability benefits.
• Flexible work model with hybrid, onsite, or virtual arrangements.
• Generous paid parental leave policies (location-dependent).
• Free access to on-site wellness centers (where available) and confidential counseling support.
• Career development and training opportunities to help you grow in your role.

Equal Opportunity Employment:

American Express is an equal opportunity employer and values diversity. We make 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.