Data Analyst (Credit Risk Modelling)

IDFC First Bank is a leading private sector universal Bank in India. Our Bank's vision is to build a world-class bank in India, guided by ethics, powered by technology, and to be a force for social good. IDFC First Bank provides a range of financial solutions to individuals, small businesses and corporations. The Bank offers savings and current accounts, NRI accounts, salary accounts, demat accounts, fixed and recurring deposits, home and personal loans, small business loans, forex products, payment solutions and wealth management services. IDFC First Bank has a nationwide presence and operates in the retail banking, wholesale banking and other banking segments.

Responsibilities:

Data Handling and Preprocessing: Perform data cleansing, merging, and enrichment, ensuring high-quality datasets for scorecard development. Handle large-scale financial datasets and transform them into actionable insights for credit risk scoring.

Feature Engineering: Extract and engineer meaningful features from raw financial data to enhance the predictive power of credit risk models. Perform advanced feature selection techniques to optimise model performance.

Risk Model Development: Build, test, and refine machine learning algorithms to predict credit risk, leveraging a mix of traditional and advanced analytical approaches.

Regulatory Compliance and Transparency: Ensure that all credit risk models comply with industry regulations and internal standards. Use best practices for model governance, ensuring transparency and traceability throughout the process.

Business Insights and Reporting: Conduct exploratory and targeted data analyses to gain actionable insights and support the development of new strategies for assessing and managing credit risk.

Model Performance Tracking: Continuously track the performance of deployed credit risk models, analyse any deviations, and ensure models meet business expectations and regulatory standards.

Key Success Metrics:

Model Accuracy and Risk Mitigation: Ensure the development and implementation of accurate credit risk models that effectively mitigate business and financial risk. Business.

Outcomes and Impact: Contribute to reducing default rates, enhancing credit approval accuracy, and driving profitability through advanced predictive analytics.

Revenue Growth and Profitability: Drive revenue growth by ensuring that credit risk models enable profitable lending decisions and support sound credit policies.

Model and Tool Development: Successfully develop and deploy credit risk models that align with business strategies and meet quality standards.

Model Optimisation and Enhancement: Continuously enhance model performance and efficiency through regular monitoring, back testing, and recalibration of models.

Strategic Campaign Design: Independently design strategies for credit risk campaigns, including credit limit adjustments, delinquency management, and credit portfolio optimisation.

Tracking and Monitoring: Regularly track and report on the performance of credit risk models to ensure they meet business and risk management goals.

Requirements:

Proven experience in developing and deploying credit risk models (e. g., Application scoring, behavioural scoring).

Solid understanding of credit risk assessment techniques, including statistical, machine learning, and traditional risk modelling approaches.

Experience in using data science and statistical software (e. g., Python, Pyspark) for data analysis and model development.

Strong communication skills, with the ability to present complex analytical results to non-technical stakeholders.

Experience in model deployment practices.

Educational Qualifications:

Graduate (Full Time): Master's/Bachelor's in Mathematics, Computer Science, Engineering, Statistics, Economics, Finance, or a related field.