AVP - Model Monitoring

3across; Dadri; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

3across in Noida, a hybrid-embedded role for experienced professionals in Model Risk Management, Validation and Monitoring within the banking/financial services domain.

You will review analytical and risk models, ensure governance across the lifecycle, and collaborate with risk, analytics, development and business teams to oversee model performance and remediation strategies.

Qualifications

• Hands-on experience in Model Risk Management, Model Validation or Model Monitoring.
• Good understanding of the model lifecycle and model governance processes.
• Strong analytical and problem-solving skills.
• Hands-on experience with Python for data analysis, statistical analysis, model validation or monitoring.
• Good working knowledge of SAS and SQL.
• Experience with large datasets and data quality/statistical analysis.
• Knowledge of statistical modelling and/or Machine Learning techniques.
• Understanding of model performance metrics and monitoring concepts.
• Experience with Git/GitLab, JIRA and Confluence is preferred.
• Exposure to DevOps tools such as Jenkins or TeamCity would be an advantage.

Responsibilities

• Perform model validation and ongoing monitoring across risk models.
• Support model lifecycle activities including development review, implementation, monitoring and periodic validation.
• Conduct model performance analyses and identify deterioration or data issues.
• Perform statistical analyses to evaluate performance and effectiveness.
• Review model assumptions, methodologies, and supporting analysis.
• Prepare validation and monitoring reports and documentation.
• Work with large datasets to perform data quality checks.
• Collaborate with Model Risk Management, Model Development, Risk, Technology and Business teams.
• Automate recurring monitoring activities where possible.
• Present findings to internal and external stakeholders.

Skills

Model Risk Mgmt

Model Validation

Model Monitoring

Python

Data analysis

Statistics

SAS

SQL

Git/GitLab

JIRA

Confluence

DevOps tools

Tools

Git/GitLab

JIRA

Confluence

SAS

SQL

Job description

Experience - 7 Years - 12 Years

Location - Noida

Work Mode - Hybrid

Role Overview:

We are looking for a professional with experience in Model Risk Management, Model Validation and Model Monitoring to support the review and oversight of analytical and risk models within the banking/financial services domain.

The role will involve working closely with risk, analytics, model development and business teams to assess model performance, identify potential risks, support validation activities and ensure appropriate model governance throughout the model lifecycle.

Key Responsibilities:

• Perform model validation and ongoing monitoring activities across different risk models.
• Support model lifecycle activities including model development review, implementation, monitoring and periodic validation.
• Conduct model performance analysis and identify deterioration, data issues or other model-related risks.
• Perform statistical and analytical assessments to evaluate model performance and effectiveness.
• Review model assumptions, methodologies, documentation and supporting analysis.
• Conduct root-cause analysis for model performance issues and support recommendations for remediation.
• Prepare and maintain validation reports, monitoring reports and model-related documentation.
• Work with large datasets to perform data quality checks and analytical assessments.
• Collaborate with Model Risk Management, Model Development, Risk, Technology and Business teams.
• Support model governance activities and ensure adherence to applicable model risk management frameworks and processes.
• Automate recurring monitoring and validation activities wherever possible using analytical and programming tools.
• Present findings and analysis to internal and external stakeholders as required.

Required Skills:

• Hands-on experience in Model Risk Management, Model Validation or Model Monitoring.
• Good understanding of the model lifecycle and model governance processes.
• Strong analytical and problem-solving skills.
• Hands-on experience with Python for data analysis, statistical analysis, model validation or monitoring.
• Good working knowledge of SAS and SQL.
• Experience working with large datasets and performing data quality and statistical analysis.
• Knowledge of statistical modelling and/or Machine Learning techniques.
• Good understanding of model performance metrics and monitoring concepts.
• Experience with tools such as Git/GitLab, JIRA and Confluence is preferred.
• Exposure to DevOps tools such as Jenkins or TeamCity would be an advantage.