Akash Patwa

About Akash Patwa

Holding a Ph.D. from the Raman Research Institute and a strong Physics background from IIT Bombay, I specialize in quantitative research, OTC derivatives, risk modeling, and algorithmic trading. My expertise includes statistical analysis, numerical simulations, and large-scale data processing. Proficient in Python, high-performance computing, and automation, I focus on building pricing models, risk assessments, and scalable analytics. Currently serving as Lead Quant Analyst at BNY, I leverage Python, MS Excel, and Bloomberg Terminal to enhance valuation accuracy and develop models for swap pricing across global markets.Senior Associate (Lead Analyst/AVP)| Bank of New York (BNY)(2023–Present)Overseeing valuation and market data controls for 10K+ OTC trades across 30+ currencies, managing $1.5B+ in daily exposure. Designed scalable Python pipelines for bulk OTC derivative valuations and anomaly detection. Conducted stress testing, model validation, and risk assessments for IRS, ZCS, and FX derivatives. Automated data acquisition from multiple vendors, reducing manual effort and enhancing efficiency. Partnered with cross-functional teams to improve valuation accuracy and expand IRS coverage across global markets.Analyst (Quantitative Research)| Stat Edge LLP (2021–2022)Designed and deployed algorithmic trading strategies across options and stock futures, including intraday, options selling, and statistical arbitrage. Managed $2M intraday capital, achieving a 40% annual return with a 5% max drawdown. Conducted high-frequency data backtesting, optimizing performance 10x through parallelization and efficient memory management. Built real-time market data pipelines and automated trading workflows using Python, APIs, and shell scripting.

Experience

1. Lead Quant Analyst AVP

   BNY

   Jan 2023 — Present · Pune, IN

   Developed Python-based valuation and market data controls for 10k+ OTC trades across 30+ currencies.• Led valuation and threshold analysis for OTC derivatives (IRS, ZCS, FXO, INF, SWO, CDS, CDX), overseeing$1.5B+ in daily exposure.• Built scalable pipelines to streamline bulk OTC derivative valuations for 100+ institutional clients.• Conducted stress testing, model validation, and risk assessments for yield curves and IRS/ZCS pricing models.• Designed NDIRS swap valuation models for emerging markets, enhancing coverage and accuracy.• Expanded IRS valuation coverage across currencies and indices, working with cross-functional internal and external teams.• Built anomaly detection and analytics tools to enhance valuation accuracy and flag data inconsistencies.• Automated data acquisition from multiple vendors via SFTP and implemented Python-Selenium scripts for testing and validation, significantly reducing manual effort and processing time.

Education

• Banaras Hindu University

  Bachelor of Science (B.Sc.), Physics

  2010 — 2013

• Raman Research Institute

  Doctor of Philosophy (Ph.D.), Cosmology and Astrophysics

  2015 — 2021

• Indian Institute of Technology, Bombay

  Master of Science (M.Sc.), Physics

  2013 — 2015