Risk Analyst

Key Responsibilities

• Retail Credit Risk Model Management and Validation:

o Lead the validation of complex underwriting, collection, and ECL models independently.

o Perform comprehensive model performance analysis and drive the investigation of model and

portfolio variances.

o Ensure that all model validation procedures meet the organization's risk assessment standards.

• Advanced Data Analysis and Reporting:

o Oversee the preparation and consolidation of key risk analysis reports and presentations for senior management committees.

o Automate and streamline reporting processes to generate actionable insights and drive value

across stakeholders.

o Ensure the accuracy and relevance of all reports and dashboards, contributing to improved

decision-making.

• Strategic Risk Insights and Advisory:

o Lead the deep-dive investigations into unusual model behaviours and portfolio performance

discrepancies, advising the business on necessary actions.

o Use advanced analytics to ensure the effective execution of risk analysis and provide strategic

insights to the business.

• Stakeholder Engagement and Technical Leadership:

o Act as a technical lead in collaborating with senior stakeholders to ensure model validation and risk management procedures align with business objectives.

o 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:

o Champion the development of a purpose-driven, high-performance culture within the team.

o Lead the training and mentoring of junior associates, supporting their professional growth and

technical expertise.

o Contribute to strategic decision-making, ensuring alignment between credit risk models and

business growth.

Education Master's 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.

• Strong 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.