Credit Risk Modeling Role - Regulatory Model - BFSI

Credit Risk Modeling( Regulatory models), Analysis of business dimensions,Critical data elements, Risk Domain

1. Ability to translate Business Problem to a Statistical Problem and Statistical solutions to a viable Business solution.

2. Ability to perform statistical modelling (predictive, regression, hypotheses testing, multivariate analysis, Time Series, Cluster, forecasting, ARIMA) using Python/Pyspark.

3. In-depth knowledge of Statistics and Machine Learning concepts and should be able to apply them to business problems

4. Experience in collaborating with technology team and support the development of analytical models with the effective use of data and analytic techniques.

5. Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), performing EDA.

6. To validate the model results, Monitor model performance, and articulate the insights to the business team.

7. Ability to create good visualization with the output generated from the model

8. Write complex SQL queries to perform data extraction from various data sources

9. Prepare client consumable presentations with actionable insights for data driven decision making.

10. Ability to build use cases for the business and present them to client as well as Project IT stakeholders

11. Self-motivated with the ability to take direction and work independently

12. Document the model requirements in a suitable doc

13. Engage with internal/external stakeholders in collaborative data science project management.

Competency Required:

1. Should have hands on experience with Machine learning models like Logistics regression, Survival analysis model, Gradient Boost, Collaborative filtering, Bayesian, SVM, Random Forest etc.

2. Prior experience in predictive model building using Python

3. Working experience in developing credit risk(regulatory) models for banks

4. Excellent knowledge of Python or SAS and other statistical tools

5. Masters Statistics/ Mathematics/ Computer Science or another quantitative field

6. Minimum 1-2 years documentation skills using GitHub based data science solution development

7. Core data sciences experience entailing programing in R/ Python, performing Exploratory Analysis and sound knowledge in statistics with a strong documentation background.