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Tier-1 brand, metro location, and mid-level role increase competition despite niche regulatory quant skill requirements.
Highly specialized banking, ALM and regulatory modeling work limits cross-industry transferability.
Explicit 4+ years, mandatory Python/R/SAS, and regulatory-modeling experience create strict shortlisting filters.
Create, implement, and document complex statistical models for market, credit, and operational risk forecasting and capital requirement computations.
Enhance and validate deposit balance sheet and asset & liability management models, ensuring adherence to model governance and regulatory requirements.
Lead stakeholder engagements including model reviews and challenges, collaborate with regulators, auditors, and business partners on analytical strategy and model use.
4+ years of Quantitative Analytics experience.
Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Mandatory programming proficiency in Python, R, or SAS.
Work Experience in Deposit balance sheet modeling and treasury/liquidity analytics, or equivalent, not explicitly limited to a minimum but desirable at 4+ years.
Experienced with econometric and statistical time series/panel data analysis relevant to banking risks and capital modeling.
Capable of managing complex model development lifecycle including validation, monitoring, implementation, and addressing regulatory feedback.
Strong documentation skills paired with ability to prioritize and communicate complex technical findings to senior management and regulatory stakeholders.