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Strong brand, mid-level ML role, metro location, and broad skillset requirements increase candidate competition.
Specialized credit-risk and regulatory modeling experience reduces transferability across industries.
Explicit 2–5 years, Master's degree, regulatory modeling and technical stack requirements make filters strict.
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Validate AI and statistical models across financial domains such as consumer/commercial credit risk, marketing, fraud, and account management to ensure accuracy and compliance.
Use Google Cloud Platform to automate workflows and improve process integration for AI validation projects.
Collaborate with departments to implement AI strategies and contribute to policy development for AI practices and model risk management.
2-5 years of experience in developing and/or validating models with industry domain knowledge.
Master’s degree or higher in Statistics, Mathematics, Engineering, Economics, Data Science, or relevant field.
Advanced programming skills in Python and SQL; experience with ML libraries such as Scikit-learn, StatsModels, TensorFlow is recommended.
Work Experience Required: 2-5 years; Location: Pune, India; Work Mode: Hybrid full-time.
Expertise in AI techniques including machine learning, NLP, and deep learning applied to financial domains.
Experience working with cloud platforms (preferably GCP) and familiarity with regulatory requirements related to model risk management.
Proven ability to collaborate across diverse teams and geographies in a structured organizational environment.