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Strong Tier-1 bank and Hyderabad mid-level role increases applicant density despite niche model-risk specialization.
Requires financial model-risk and regulatory expertise, limiting transferability across industries despite ML skills.
Requires 4+ years, a quantitative Master's, and specialized model-risk/NLP/GenAI expertise, making filters strict.
Validate NLP/GenAI models within Model Risk Management by assessing model methodology, data integrity, development, performance, and compliance.
Manage model risk lifecycle activities including risk ranking, validation, change management, and performance monitoring for quantitative models.
Develop, evaluate, and deploy internal validation tools and provide guidance on model risk management best practices across the community.
4+ years of quantitative analytics experience or equivalent through work, training, military experience, or education.
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Experience with NLP/GenAI or Agentic models and exposure to model risk management policies, preferably in financial domain.
Work Experience Required: 4+ years of Quantitative Analytics experience.
Deep expertise in advanced quantitative modeling, statistical theory, and managing model risk in a regulated financial environment.
Experienced with software engineering or scientific computing, including recent frameworks for ML, GenAI, and Agentic pipelines.
Strong communicator able to produce detailed technical validation reports understandable to auditors, regulators, and technical stakeholders.