Analyst-Data Science

Role Overview

Responsibilities

• Support independent oversight and challenge of GenAI, LLM-based, and advanced ML models.
• Participate in risk-based reviews of model design, training data, prompt design, assumptions, performance, monitoring, and controls.
• Assess bias, explainability, robustness, and misuse risks.
• Execute model risk testing, documentation reviews, and evidence assessment under MRMG standards.
• Perform policy and regulatory gap assessments for AI/ML models.
• Research AI/ML, GenAI, AI risk management, and regulatory developments.
• Prepare analysis, validation notes, and risk summaries for stakeholders.
• Communicate findings to business partners, model committees, and senior leaders with manager guidance.
• Collaborate with data science, engineering, product, and risk teams on validation execution.
• Improve scalable GenAI risk management practices and MRMG process quality.

Qualifications

• MBA or master's degree in a listed quantitative discipline from a top-tier institute.
• 0–2 years of relevant analytics, data science, model development, validation, or big-data experience.
• AI/ML development, testing, or validation exposure through work, projects, or internships is preferred.
• Generative AI or LLM exposure is a strong plus.
• Hands-on experience with at least one of Python, PySpark, R, or SQL is required.
• Requires analytical, problem-solving, communication, prioritization, and adaptability skills.

Benefits

• Benefits include competitive base salary, bonus incentives, and financial well-being and retirement support.
• Medical, dental, vision, life, and disability benefits may apply depending on location.
• Working arrangements may be hybrid, onsite, or virtual depending on the role and business need.
• Includes parental leave, wellness centers, counseling support, and career development opportunities depending on location.