*Conducted end-to-end qualitative assessments of Value at Risk(VaR) models, including stressed VaR and Expected Shortfall(ES), delivering key findings to clients as part of the MRM team.*Performed in-depth validation of market risk models, comparing methodologies such as Historical Simulation, Parametric, and Monte Carlo, ensuring accuracy and robustness in model outputs.*Executed quantitative analysis through back-testing, sensitivity analysis, and stress testing to assess model performance and compliance with regulatory requirements.*Worked on IFRS 9 audit support for middle East banks, providing quantitative analysis of expected credit loss and PD, LGD, EAD implementation under IFRS 9 guidelines.

Serving as a subject matter expert for “Probability and Statistics” on chegg.com, solved 200 queries and problems and got rated with average 80% CF score.

work on developing and testing statistically-based quantitative long short market neutral portfolio's (medium-frequency equities) trading strategies in python (pandas and sklearn).completed research on 10 research papers and ideas with high sharpe ratio and abnormal returns (Perform statistical analysis of large sets of financial data.perform data modelling, evaluations and simulations).Researching portfolio construction to efficiently weight alphas and manage risk.

* Worked on Risk Metric evaluation and computation of three different portfolio performances to get close to actual performance result provided by MSCI Benchmark* India S2 Quant Model- Developed an India specific quant model with the factors used in CapIQ, which involved factor selection, ranking of assets and generating ALPHA coefficient for respective quant portfolio model.

Analysed the past behaviour of 10 years sales/demand time series data and observed the Trend, Seasonality, and Irregularity of the given set of dataQuantitatively estimated the forecast by applying the Moving Average concept, regression analysis & Time series analysis method.