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Om Umare

Quantitative Research Specialist — London Stock Exchange Group

Charlotte, NC · umareh@gmail.com · linkedin.com/in/omumare · github.com/umareh

Summary

Quantitative researcher and ML engineer with 3+ years across options market-making, derivatives pricing, and production analytics. Designs and deploys pricing models for complex instruments, builds low-latency real-time applications, and owns CI/CD for client-facing systems. CFA Level II candidate; two IEEE publications in deep learning.

Experience

London Stock Exchange GroupJun 2023 – Present · Charlotte, NC

Quantitative Research Specialist (promoted March 2026 from Senior Quantitative Research Analyst)

  • Design and deploy ML models for pricing and valuation across complex financial instruments
  • Build low-latency, real-time applications for asset evaluation and risk analytics
  • Lead a scalable analytics platform (Python, SQL, React, Docker, Azure) used by trading and risk teams
  • Own CI/CD pipelines for high-impact, client-facing production applications
Group OneMar 2022 – Sep 2022 · New York, NY

Trading Analyst

  • Trading Analyst working directly with market makers on equities and options
  • Developed automated trading technology, strategy backtests, and pricing/risk/capital models
  • Tested SABR, GARCH, and stochastic-volatility models for options market-making
VenerableMar 2021 – Sep 2021 · West Chester, PA

Quantitative Pricing Analyst · Insurance pricing & risk management

  • Insurance pricing and risk management — futures, swaptions, Treasuries, options, and bonds
  • Elevated Futures Pricer model (C#) with cross-functional dev team; migrated data to ETL-based SQL architecture

Education

Drexel University — Philadelphia, PAGPA 3.8

M.S. Machine Learning Engineering · B.S. Computer Engineering · Minor in Mathematics and Finance

Credentials

CFA Level II Candidate (sat May 2026) · CFA Level I Passed (2024) · SIE (2023)

Skills

Technical: Python, SQL, C++, Rust, JavaScript, R, C#, MATLAB · Machine Learning, PyTorch · Docker, Azure, AWS, CI/CD, React, Flask, Streamlit

Finance: Options pricing, Volatility modeling (SABR / GARCH / SV), Fixed income, Derivatives, Risk models, Yield curves, Backtesting

Publications

  • An Overview of Deep Learning in UAV Perception — IEEE ICCE 2024, Las Vegas
  • Long-Range Drone Detection Dataset — IEEE ICCE 2024, Las Vegas

Selected projects

  • Options Strategy Terminal — multi-leg builder with live chains, IV skew, Black-Scholes Greeks, payoff diagrams
  • Portfolio API — Flask REST service (quotes, chains, expirations, market snapshots) deployed on Render
  • Curiosity Index — parsed 13,655 videos of watch history into an interactive topic graph