Analyst-Data Science

Responsibilities

• GenAI Model Risk Assessment & Oversight
• Support independent oversight and effective challenge of Generative AI, LLM‑based, and advanced ML models across the enterprise.
• Participate in risk based GenAI model risk reviews, including assessment of: Model objectives, design, and architecture Training data, prompt design, and assumptions Model performance, monitoring approaches, and control mechanisms Risks related to bias, explainability, robustness, and misuse
• Model objectives, design, and architecture
• Training data, prompt design, and assumptions
• Model performance, monitoring approaches, and control mechanisms
• Risks related to bias, explainability, robustness, and misuse
• Execute model risk testing, documentation reviews, and evidence assessment in line with MRMG standards.
• Frameworks, Research & Continuous Learning
• Contribute to gap assessments against internal policies and external regulatory expectations for AI/ML models.
• Conduct AI/ML and GenAI research to support MRMG guidance, standards, and validation approaches.
• Stay current on emerging trends in Generative AI, AI risk management, and regulatory developments , and apply learnings to day‑to‑day work.
• Stakeholder Collaboration & Communication
• Prepare clear, well‑structured analysis, validation notes, and risk summaries for internal stakeholders.
• Communicate analytical findings effectively to business partners, model committees, and senior leaders , with guidance from managers.
• Collaborate with cross‑functional teams including data science, engineering, product, and risk partners to support validation execution.
• Enterprise Contribution
• Support consistent, scalable, and defensible GenAI risk management practices across the enterprise.
• Help improve efficiency and quality of MRMG processes through strong analytical execution and documentation discipline.
• Critical Factors to Success
• Business & Enterprise Outcomes
• Contribute to improved model accuracy, robustness, and governance for GenAI and ML models.
• Support enterprise objectives by enabling responsible AI deployment through strong risk discipline.
• Continuously improve technical and domain expertise to enhance business impact.
• Enterprise Leadership Behaviors
• Set the Agenda Demonstrate enterprise thinking and connect work outputs to broader risk and business priorities.
• Demonstrate enterprise thinking and connect work outputs to broader risk and business priorities.
• Bring Others With You Collaborate effectively, seek feedback, and actively contribute as part of high‑performing teams.
• Collaborate effectively, seek feedback, and actively contribute as part of high‑performing teams.
• Do It the Right Way Communicate clearly and candidly, demonstrate integrity in analysis, and uphold American Express values. Show learning agility, curiosity, and willingness to challenge assumptions responsibly.
• Communicate clearly and candidly, demonstrate integrity in analysis, and uphold American Express values.
• Show learning agility, curiosity, and willingness to challenge assumptions responsibly.

Qualifications

• Education
• MBA or Master’s Degree in Statistics, Economics, Data Science, AI/ML, Generative AI or related quantitative fields from a top‑tier institute.
• Experience
• 0–2 years of experience in analytics, data science, model development, validation, or big‑data workstreams.
• Exposure to AI/ML model development, testing, or validation through professional experience, projects, or internships preferred.
• Interest in or early exposure to Generative AI or LLM‑based systems is a strong plus.
• Technical Skills
• Foundational understanding of AI/ML concepts , with interest in Generative AI technologies.
• Hands‑on experience with at least one of Python, PySpark, R, or SQL .
• Ability to work with data, perform analytical checks, and support model evaluation activities.
• Core Capabilities
• Strong analytical, problem‑solving, and structured‑thinking skills.
• Clear written and verbal communication, with ability to explain analytical results to diverse audiences.
• Ability to manage multiple tasks, adapt to changing priorities, and meet tight timelines.

About Company

Company