Analyst, Data Science

Responsibilities

• Support independent oversight and effective challenge of Generative AI, LLM-based, and advanced ML models across the enterprise.
• Participate in risk-based GenAI model reviews, assessing model design, training data, prompt design, and performance monitoring.
• Execute model risk testing, documentation reviews, and evidence assessment in line with MRMG standards.
• Conduct research on emerging trends in Generative AI and AI risk management to support internal guidance and standards.
• Prepare clear analysis, validation notes, and risk summaries for business partners and senior leadership.
• Collaborate with cross-functional teams including data science, engineering, and product to support validation execution.

Requirements

• MBA or Master’s Degree in Statistics, Economics, Data Science, AI/ML, or related quantitative fields.
• 0–2 years of experience in analytics, data science, model development, or validation.
• Foundational understanding of AI/ML concepts and interest in Generative AI technologies.
• Proficiency in at least one of the following: Python, PySpark, R, or SQL.
• Strong analytical, problem-solving, and structured-thinking skills.
• Excellent written and verbal communication skills for explaining technical results to diverse audiences.

Preferred Qualifications

• Professional experience, projects, or internships involving AI/ML model development or testing.
• Early exposure to Generative AI or Large Language Model (LLM) based systems.

Benefits

• Competitive base salaries and bonus incentives.
• Comprehensive medical, dental, vision, life insurance, and disability benefits.
• Flexible working model with hybrid arrangements.
• Support for financial well-being and retirement.
• Generous paid parental leave policies.
• Career development and training opportunities.

About the Company

American Express is a global leader in payments and financial services, built on a 175-year history of innovation and trust. We are committed to backing our customers, communities, and colleagues through responsible innovation and a strong risk mindset.