We are looking for Regulatory model development with one of our top financial Institution.
Exp: 2-7 yrs
Quant Analyst/ Sr Quant Analyst
Education: Master's degree required.
Job Location: Hyderabad
In this role, you will:
- Perform highly complex activities related to creation, implementation, and documentation
- Use highly complex statistical theory to quantify, analyze and manage markets
- Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives.
- Utilize structured securities and provide expertise on theory and mathematics behind the data
- Manage market, credit, and operational risks to forecast losses and compute capital requirements.
- Participate in the discussion related to analytical strategies, modeling and forecasting methods.
- Identify structure to influence global assessments, inclusive of technical, audit and market perspectives.
- Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills
Required Qualifications:
- Overall experience of 2-8 years in Risk Analytics
- Degree in applied mathematics, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis.
Strong Quantitative Skills:
- 3+ years of Predictive modeling experience. Good understanding of model development and model testing.
- Proficient in statistical analysis
- Good Problem Solving and Analytical Skills
- Programming Skills
- 2+ years of hands on experience in Python and SQL
- 1+ years of experience in SAS
- Good Written and Oral Communication Skills
Job Expectations:
- Development of regulatory Credit risk (including CCAR, CECL and IFRS), RRP Valuation, and PPNR models for Commercial portfolio in SAS/Python.
- Migration of existing development/implementation codes from SAS to Python with thorough testing and UAT
- Work closely with onshore team to understand and enhance the data and modeling process behind existing models, develop new models, address data and model issues/findings.
- Underlying portfolio data research and analytics using strong programming skills
- Adhere to audit and model validation governance to ensure data and modeling process are in compliance with policy and are working as intended, address model validation and regulatory feedback issues
- Support ad-hoc analytic projects.
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