Key Responsibilities:

- Retail Credit Risk Model Management and Validation:
- Lead the validation of complex underwriting, collection, and ECL models independently.
- Perform comprehensive model performance analysis and drive the investigation of model and portfolio variances.
- Ensure that all model validation procedures meet the organizations risk assessment standards.
- Advanced Data Analysis and Reporting:
- Oversee the preparation and consolidation of key risk analysis reports and presentations for senior management committees.
- Automate and streamline reporting processes to generate actionable insights and drive value across stakeholders.
- Ensure the accuracy and relevance of all reports and dashboards, contributing to improved decision-making.
- Strategic Risk Insights and Advisory:
- Lead the deep-dive investigations into unusual model behaviours and portfolio performance discrepancies, advising the business on necessary actions.
- Use advanced analytics to ensure the effective execution of risk analysis and provide strategic insights to the business.
- Stakeholder Engagement and Technical Leadership:
- Act as a technical lead in collaborating with senior stakeholders to ensure model validation and risk management procedures align with business objectives.
- Provide expert guidance to junior team members, ensuring the team adheres to best practices in model validation and risk analytics.




- Leadership in Team Development and Culture Building:
- Champion the development of a purpose-driven, high-performance culture within the team.
- Lead the training and mentoring of junior associates, supporting their professional growth and technical expertise.
- Contribute to strategic decision-making, ensuring alignment between credit risk models and business growth.

Eligibility Criteria for the Job Education Masters Degree in Statistics, Economics, Mathematics, Engineering; MBA

Experience 6 to 9 Years of relevant experience

Skills & Competencies

- Strong expertise in coding with Python, SQL, and optionally SAS..
- Advanced knowledge of MS-Office Suite, with expert skills in data analysis
- and visualization tools.
- • In-depth experience in analysing and validating credit risk scorecards and
- bureau data.
- • Robust capability in investigating and analysing significant variances in MI and
- model performance.
- • Expertise in advanced machine learning models like Gradient Boosting,
- Neural Networks, Random Forest, etc. is highly preferred.
- • Strong understanding of Data Warehouse, Cloud Data platforms, and their
- integration with model validation.
- • Strong leadership and project management skills, with the ability to influence
- and guide team members and business stakeholders.

📌 Analytics Model Validation (Delhi)
🏢 Hero FinCorp
📍 Delhi