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Tiger Analytics
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Quantitative Risk and Model Validation Analyst

Quantitative Risk and Model Validation Analyst

Tiger Analytics

3 - 7 years

0 Lacs

hyderabad telangana

Posted:11 hours ago| Platform: Shine logo

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Skills Required

econometrics statistics regression analysis time series analysis optimization risk models optimization algorithms sas python sql machine learning exploratory data analysis quantitative methods

Work Mode

On-site

Job Type

Full Time

Job Description

You will be responsible for designing and validating mathematical models used by the bank and conducting mathematical analysis of the data in the Market Risk and Counterparty Credit Risk division. Your role will involve analyzing and building sector/industry risk assessment mathematical methodologies and quantitative measurement techniques for the assessment of credit risk exposures and evaluation of structured products. **Key Responsibilities:** - Monitor and validate aggregate model risk in alignment with the bank's risk strategy - Lead a team of Model validators who review and validate a wide variety of models using predictive and AI Modeling knowledge - Manage a growing Model Validation team responsible for independent first-line validation of predictive and generative AI models - Perform independent validations of financial, statistical, and behavioral models based on their criticality ratings - Assist with the validation and review of models regarding their theoretical soundness, testing design, and points of weakness - Interpret data to identify potential risk exposure - Develop challenger models to validate existing models and assist with outcome analysis - Ensure compliance with the model risk monitoring framework - Evaluate governance for Model Risk Management by reviewing policies, controls, risk assessments, documentation standards, and validation standards - Exposure to CCAR/CECL/IRB Models is preferred - Evaluate the Bank's compliance with SR 11-7 regulatory guidance You should have the following qualifications: - Education: Graduate/Master degree in computer science, statistics, econometrics, mathematics, computational finance, or similar - Deep knowledge in Quantitative methods/econometrics/statistics - Strong in Regression analysis, Time series Analysis, optimization - Knowledge of Risk Models and Optimization algorithms - Good working knowledge of SAS, Python, and SQL, Machine learning, exploratory data analysis (Note: Any additional details about the company were not provided in the job description.),

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Quantitative Risk and Model Validation Analyst