Are you a pro at statistical modelling along with a deep understanding of Credit Risk in financial services? If yes, here is an opportunity to join a fast-paced, challenging, and entrepreneurial environment of Valiance Solutions. Have a look.
Designation – Credit Risk Modeller
Location – Noida
About employer – Valiance Solutions
The position offers a unique opportunity to be part of a small fast-paced, challenging, and entrepreneurial environment with a high degree of individual responsibility. Significant opportunities for professional development exist, as we continue to grow.
Seasoned Credit Risk Modeller for Decision sciences team of Valiance Solutions.
- Develop, maintain and optimize statistical models for various risk scenarios. Some of the models
- Credit Default Model
- Credit Scorecards
- Loss Given Default
- Basel Modelling
- Lead and manage team of Business Analysts in successful delivery of analytics projects
- Managing client satisfaction, feedback process, managing/tracking workflow
- Drawing actionable recommendations from data for senior management
Qualification and Skills Required:
- 4 year Bachelor’s or Master’s degree from reputed University with concentration on marketing, finance, economics or other quantitative field such as statistics or engineering.
- 2-4 years of experience in advance analytics within banking sector
- Have extensive analytical/statistical knowledge such as modelling, cluster analysis, Logistic regression, neural networks, Linear regression, time series forecasting, Random Forest
- Good theoretical and practical knowledge of tools SAS, R, SPSS, SQL, VBA etc.
- Ability to comprehend intricate and diverse range of business problems and analyze them with limited or complex data and provide a feasible solution framework
- Understanding of Credit Risk concepts in financial services domain
- Experience in Credit Risk Modelling including knowledge of variables involved
Interested candidates can send their CV’S to email@example.com with subject as Risk Modeller– Valiance Solutions.