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Strong employer brand, mid-level experience band, and metro Hyderabad increase candidate competition.
Model risk management for credit/fraud in banking is highly domain-specific and not easily transferable.
Explicit 2+/4+ year minima, mandatory MRM/domain experience, and technical stack requirements increase selectivity.
Conduct full scope model validation and ongoing performance monitoring of customer facing credit risk, fraud risk, loss forecasting, and recovery models including statistical, machine learning, and non-statistical models.
Evaluate data quality, methodology, conceptual soundness, and perform model performance testing such as back-testing, sensitivity analysis, and benchmarking for both internal and vendor-developed models.
Document validation findings, support discussions for decision making, and write detailed validation reports while supporting additional book of work or special projects as required.
Bachelor’s degree with at least 2 years of hands-on modeling experience in customer facing models such as credit, fraud, marketing, or loss forecasting; or 4+ years of relevant experience without degree.
Minimum 2 years experience developing/validating credit models using statistical tools like SAS, Python, SQL.
Minimum 2 years experience working with large data sets for statistical and ML modeling within banking or financial industry.
Work Timings require availability between 06:00 AM – 11:30 AM ET (US Eastern Time) for meetings, based in India with flexibility otherwise.
Experienced in model risk management (MRM) with strong knowledge of regulatory requirements (SR 26-2) related to model validation in financial services.
Skilled in programming languages and tools including Python, Spark, SAS, SQL, AWS, and Data Lake with experience managing large or complex datasets for statistical analysis.
Strong familiarity with consumer finance or credit card products and risk models, with a background supporting governance and independent validation functions.