Satan 48

Quantitative Trader and Researcher with a background in designing and managing systematic index options portfolios using low latency python trading infrastructure. Proven track record of generating consistent risk adjusted returns ($2M AUM, 2.8 Sharpe, NYSE and CBOE exchange) through index options trading, Greeks management, and rigorous backtesting/simulation

Quantitative Trader at AlgoEdge (2023-12 – Present)

• Systematic Index options strategy: Built and deployed a fully systematic index options trading operation, overseeing the end to end transition from initial strategy ideation and rigorous backtesting/simulation to live market execution
• Quantitative Research: Researched on term structure skew in Index options during volatility shocks. Identified and validated converging patterns using correlation analysis, out of sample validation and walk forward analysis. Designed hedge trades to account for gamma exposure / convexity risks
• Portfolio Ownership: Managed a portfolio with $2M AUM; delivered 19% absolute returns (Apr 2025 – now) with a 2.8 Sharpe ratio (in NYSE and CBOE exchanges) maintaining absolute ownership of PnL and real time risk / greek exposures
• Market Regime Research: Built a Decision Tree model to classify market regimes using multi frequency IV/RV features (implied/realised volatility). Improved strategy resilience by identifying high risk environments, cutting maximum drawdown from 18% to 8%
• Infrastructure Management: Oversaw the firm's proprietary low latency trading framework using ArcticDB and broker APIs to achieve sub 300ms data to execution cycles. Oversaw development of a customized reporting interface for clients to provide real time transparency into capital deployment and strategy specific performance analytics

Strategy & Operations Associate at slice (2023-04 – 2023-11)

• Systems Optimization: Directed an infrastructure project to integrate new server systems and API middleware, achieving >99% uptime and drastically reducing latency across the end to end loan disbursement lifecycle from customer acquisition to payout
• Liquidity & Redundancy Engineering: Developed a dynamic fund routing algorithm to manage capital distribution across multiple banking nodes, ensuring continuous loan disbursement by automatically rerouting transfers during server outages or partner downtime.
• Stakeholder Management: Navigated complex integrations by collaborating cross functionally with engineering, product, and external vendors to ensure system robustness.

Market Risk Quant (Commodities) at Goldman Sachs (2021-06 – 2023-04)

• Risk & Regulatory Strategy: Managed the end to end Value at Risk (VaR) calculation logic and stress-testing benchmarks for commodities ensuring alignment with FRTB (Fundamental Review of the Trading Book) and internal risk mandates.
• Quantitative Modeling & Risk Estimation: Applied Expectation Maximization (EM) algorithms to backfill incomplete asset time series, significantly enhancing the precision of VaR calculations for emerging and illiquid commodities.
• Risk Factor Analysis: Utilized Principal Component Analysis (PCA) to identify and isolate key risk drivers, enabling the calibration of volatility shocks within the Heston model framework for commodities and the Hull White framework for interest rate swaptions
• Data Migration: Led the migration of legacy database systems to cloud-based architectures, significantly enhancing data accessibility and retrieval efficiency for global trading desks

BTech in Mechanical Engineering Core – Indian Institute of Technology (IIT) Delhi (2021)