Discipline: Banking
Subsector: Analytics
Location: Bangalore
About our Client: Our Client is a large MNC bank with market leading position in retail banking products like credit cards, mortgage, auto loans etc. across all major markets in which they operate. As part of expansion of their global analytics team, they are looking for a seasoned analytics professional who can play a critical role in their Analytics team developing Quantitative and Predictive models and support the global team.
Job Description: Reporting in to the Business Head, you will be responsible for:
- Building Loss distribution models to quantify risk as a part of Basel 2 Capital project for the Retail asset portfolio of the bank using advance analytical techniques like correlation modeling, loss distribution fitting, Monte Carlo simulation etc.
- Model Validation and Model Governance to ensure data integrity and confirmation to global Regulatory Guidelines
- Consult with business partners to develop and implement statistical solutions and models.
- Model monitoring and making recommendations on model performance
- Contribute to Model Development Efforts while working with senior stakeholders
The Successful Candidate: As the Successful Applicant, you will have:
- 5-8 Years of experience in Statistical Modeling or Predictive Modeling using SAS
- You must have a strong Academic Background with Masters or Bachelor's Degree in Statistics, Engineering or other Statistical Disciplines. Candidates with Bachelor's from IITs or MBA from IIMs will be preferred
- Excellent communication and interpersonal skills
- Prior experience in the Financial Services is preferred
What's on Offer:
- This is an excellent opportunity to develop your career with one of the top Global Banks. They provide an excellent career path and a high level of internal mobility (internationally) for the successful employees.
- Our client also offers a dynamic and exciting work environment with challenging work. Candidates with the right attitude and experience will be offered a highly competitive package.
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