Lead Quantitative Analytics Specialist

Overview

Lead complex credit risk modelling initiatives for the retail and commercial portfolios, covering model creation, validation, documentation and regulatory engagement.

What you'll do

• Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defence of highly statistical theory.
• 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 stochastic, structured securities and spread analysis, with expertise in the theory and mathematics behind the analysis.
• Review and assess models inclusive of technical, audit, and market perspectives.
• Manage market, credit, and operational risks to forecast losses and compute capital requirements.
• Participate in discussions 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 technically oriented individuals.
• Develop regulatory credit risk models (including CCAR, CECL and IFRS), RRP valuation, and PPNR models for the commercial portfolio in SAS/Python.
• Work closely with team members to understand and enhance the data and modeling process behind existing models, develop new models, and address data and model issues/findings.
• Conduct underlying portfolio data research and analytics using strong programming skills.
• Adhere to audit and model validation governance to ensure data and modeling processes are compliant with policy and working as intended, and address model validation and regulatory feedback issues.
• Support ad-hoc analytic projects.

What you'll need

• 5+ years of quantitative analytics experience, or equivalent demonstrated through work experience, training, education, or a combination of these.
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
• Experience in development of regulatory models (including CCAR, CECL and IFRS), RRP valuation, and PPNR models for the commercial portfolio.
• Good written and oral communication skills.
• Ability to prioritize work, meet deadlines, achieve goals and work under pressure in a dynamic and complex environment.
• Detail oriented, results driven, and able to navigate a quickly changing and high demand environment while balancing multiple priorities.
• Understanding of bank regulatory data sets and other industry data sources.
• Exposure to banking domain with strong functional knowledge in the credit risk area on the commercial portfolio.
• 5+ years of predictive modeling experience.
• Good understanding of model development and model testing.
• Proficient in statistical analysis.
• Good problem solving and analytical skills.
• 2+ years of hands-on experience in Python and SQL.
• 2+ years of experience in PySpark, GCP, and parallel processing.
• Comfortable with Git, GitHub and UNIX commands.

Details

• Location: Bengaluru, India.
• Shift timings: 1:30 PM to 10:30 PM.
• In-office expectation: 4 days a week.