Mar 2024 – Jul 2025 · 1 yr 4 mos · Mumbai, Maharashtra, India · On-site

• Reviewed and enhanced the Quantitative Impact Study (QIS) codebase across FRTB-SA (all asset classes and risk types), IMA, DRC, and RRAO, applying best practices in model implementation, automation, and performance tuning.
• Worked on parallelization and vectorization of Monte Carlo simulations for FRTB-IMA, reducing computation time from ~24 hours to ~30 minutes for large trading portfolios and making QIS runs operationally viable.
• Designed and built Python-based capital calculation engines for Securitization CTP and non-CTP portfolios, enabling consistent, audit-ready capital numbers under FRTB.
• Developed QIS tools in Python to support pre and post-trade risk analysis across Equity, Credit, FX, and Rates desks, helping traders optimize trade structures while meeting FRTB capital and eligibility constraints.
• Performed end-to-end testing, validation, and regression checks on the QIS and risk engines, improving robustness, explainability, and confidence in reported capital numbers.
• Worked closely with traders and risk managers on live desk queries to compute sensitivities (delta, vega, curvature) and pricing for complex derivatives (CDOs, CDS, and structured IR/FX/Equity options) under FRTB IMA Full Val/Greeks/2D grid frameworks.
• Prepared QIS analysis packs and impact summaries for senior stakeholders, clearly articulating capital impacts, model assumptions, and risk drivers to Trading, Market Risk, and Model Risk Management teams.
• Tech Stack & Skills:
• ✔ Python (NumPy, Pandas, SciPy), Vectorization & Parallel Computing
• ✔ Monte Carlo Simulation, VaR (IMA), QIS Automation
• ✔ FRTB-SA & IMA ES and DRC, SA-DRC, RRAO, Securitization (CTP & non-CTP)
• ✔ Derivative Pricing (CDOs, CDS, Structured IR/FX/Equity Options)
• ✔ Model Risk, Market Risk Analysis & Stakeholder Reporting

Dec 2022 – Mar 2024 · 1 yr 3 mos · Mumbai, Maharashtra, India · On-site

• Performed valuation adjustments, Greek recalculations, and P&L simulations for structured trades and exotic products, automating data pipelines in Python (NumPy, Pandas, Flask) and reducing manual analysis time by ~30%.
• Partnered with trading desks and Market Risk teams to document and validate pricing methodologies and capital charge calculations (Sensitivities, DRC, RRAO), ensuring consistency across US, UK, and APAC regulatory jurisdictions.
• Collaborated with Trading and Risk teams on FRTB-SA implementation, focusing on accurate sensitivity generation, trade risk classification, and capital attribution across multiple asset classes.
• Led the identification, categorization, and mapping of risk factors for Equities, Credit, FX, Rates, and Commodities, aligning risk factor eligibility and bucketing with FRTB-SA standards.
• Analyzed the full trade population across asset classes and proposed an optimized risk taxonomy to improve risk bucketing, correlation aggregation, and capital computation under FRTB-SA aggregation rules.
• Worked directly with traders and risk managers to validate risk factor mappings, clarify complex trade risk profiles, and ensure accurate sensitivity attribution for structured and exotic products.
• Authored Business Requirements Documents (BRDs) and methodology papers covering Sensitivity calculations, Default Risk Charge (DRC) modelling, Look-Through Approaches, and Residual Risk Add-On (RRAO), supporting regulatory compliance across US, UK, Singapore, South Africa, South Korea, and China.
• Tech Stack & Skills:
• ✔ Python (NumPy, Pandas, Flask)
• ✔ FRTB-SA, DRC, RRAO, Capital Charges
• ✔ Derivative & Exotic Product Pricing
• ✔ Market Risk Analytics & Risk Taxonomy Design
• ✔ Regulatory Documentation (BRDs, Methodology Papers)

Feb 2021 – Dec 2022 · 1 yr 10 mos

• Developed and implemented stress testing models for risk assessment using Python, NumPy, Pandas, and Scikit-Learn, optimizing model accuracy and performance.
• Enhanced computational efficiency by automating risk calculations and reporting pipelines, reducing processing time through optimized vectorized operations and parallel computing using Numpy and Pandas.
• Led research, prototyping, and development of risk modeling techniques to improve credit risk and counterparty exposure assessments for Default Fund Risk with Central Clearing Counterparties.
• Optimized model development frameworks through independent variable correlation analysis and assumption testing, improving the accuracy of credit risk exposure calculations
• Provided ad-hoc quantitative analysis and valuation of exotic financial instruments for Desk Traders, using pricing models and risk metrics computation.
• Collaborated with Credit and Market Risk Managers to ensure compliance with regulatory frameworks and validate exposure calculations, enhancing reporting accuracy.
• Developed detailed technical documentation and model reports for presentation to Senior Management, improving transparency and auditability.
• Introduced best industry practices and participated with Senior Leadership on the strategic decision making for data quality issue resolution.
• Drove cross-functional collaboration with Business and IT teams, ensuring smooth end-to-end implementation of quantitative models and strategic changes.
• Recognized with 5 RAVE GOLD BARS for excellence in Meritocracy, Partnership, and Stakeholder Management.
• Tech Stack & Skills:
• ✔ Python, NumPy, Pandas, Scikit-Learn, TensorFlow, SQL
• ✔ Risk Modeling, Monte Carlo Simulations, Stress Testing
• ✔ Credit Risk, Market Risk
• ✔ Derivatives Pricing, Time Series Analysis
• ✔ Risk Analytics & Portfolio Optimization
• ✔ Regulatory Guidelines BCBS, FRTB, CCAR, NPR
• ✔ Capital calculation and Capital Optimization
• ✔ Automation & Efficiency Improvement

Jun 2019 – Jan 2021 · 1 yr 7 mos

• Conducted Portfolio Analysis and Instrument Pricing using a Sensitivity-Based Approach, leveraging VBA, SQL and excel based spreadsheets to automate the analysis process.
• Contributed to Credit Scenario Stress Testing, CCAR Validations, and Country Risk Analysis, improving the accuracy of exposure assessments by incorporating advanced data quality check algorithms.
• Computed and analyzed credit risk exposure for Securitized Financing Trades and OTC Derivatives, enhancing risk forecasting and capital planning efficiency.
• Developed automated tools at Counterparty level to track limit breaches and exposure mismatches, reducing manual intervention and improving real-time risk oversight.
• Performed deep-dive trade-level analysis to identify risk recapture opportunities and optimize credit limits, ensuring better risk-adjusted returns.
• Identified and remediated data quality issues, implementing automated validation checks using VBA and SQL, reducing data inconsistencies.
• Automated weekly and monthly reporting processes using Python and VBA, reducing analysis time by improving efficiency in regulatory reporting.
• Led QAT testing for methodology changes, ensuring seamless integration of new risk methodologies and reducing operational errors in model execution.
• Collaborated with senior risk managers and stakeholders to provide strategic insights on portfolio holdings for credit and market exposure management and risk mitigation.
• Recognized with 9 RAVE GOLD BARS for excellence in Stakeholder Management, Accountability, and Transparency.
• Tech Stack & Skills:
• ✔ Python, Pandas, NumPy, SQL, VBA
• ✔ Portfolio Analysis, Sensitivity-Based Risk Modeling
• ✔ Credit Stress Testing, CCAR, Country Risk Assessment
• ✔ Risk Monitoring, Surveillance, and Limit Management
• ✔ Data Quality Remediation & Automation

Jul 2018 – Dec 2018 · 5 mos · Pune, Maharashtra, India

• Assisted in Stress Testing & Portfolio Analysis, evaluating market and credit risk impacts under adverse scenarios using SQL and VBA-driven automation.
• Analyzed limit breaches across portfolios, identifying key risk drivers and suggesting risk mitigation strategies to ensure compliance with risk appetite.
• Developed SQL-based automated reports to track portfolio exposures, reducing manual effort by 30% and improving reporting accuracy.
• Performed data extraction and validation from risk databases, ensuring data integrity for stress testing and credit risk analysis.
• Contributed to credit exposure analysis, assessing potential counterparty risks and assisting in trade-level reviews for high-risk positions.
• Supported scenario analysis for CCAR and internal stress testing, ensuring accurate computation of risk metrics and exposure fluctuations.
• Automated portfolio monitoring processes using VBA macros, streamlining the identification of exposure mismatches and reporting inconsistencies.
• Collaborated with senior risk analysts and credit officers, gaining exposure to real-world risk management challenges and enhancing problem-solving skills.
• Tech Stack & Skills:
• ✔ SQL, VBA, Excel Automation
• ✔ Stress Testing & CCAR Analysis
• ✔ Portfolio Risk Monitoring & Limit Breaches
• ✔ Credit Exposure & Counterparty Risk Analysis

May 2018 – Jul 2018 · 2 mos

May 2017 – Jul 2017 · 2 mos · Goa

Apr 2017 – May 2018 · 1 yr 1 mo · Pilani

Sep 2016 – May 2018 · 1 yr 8 mos

Sep 2015 – May 2018 · 2 yrs 8 mos · BITS Pilani