KMKanav Mehta
Quantitative Researcher
Master of Financial Engineering candidate at UCLA Anderson with a strong background in quantitative research, machine learning, and financial modeling. Proven experience in developing and backtesting trading strategies, with a passion for applying advanced computational methods to financial markets.
Quantitative Profile
Work Experience
Quantitative Researcher
Quanta Ventures (Remote)
Jun 2025 – Present
- Developed trading strategies for Bitcoin ETFs (BITI, IBIT & GBTC) using a sliding LightGBM with linear trees model framework incorporating various oscillator signals, EWMA, RSI, Amihud, Lottery, bid-ask spreads, SPY trend indicators among others, achieving a backtested Sharpe above 3.0.
BRAIN Research Consultant
WorldQuant (Remote)
Feb 2025 – Jun 2025
- Designed and backtested 35+ intraday, high, low, and medium-frequency trading strategies across USA, China, Europe, and UK indices, achieving Sharpe Ratios above 1.25 even after controlling for turnover.
- Developed and combined factor and timing based strategies, leveraging fundamental, price/volume, short interest, news, and options data, resulting in Sharpe Ratios exceeding 2.5 in backtesting.
- Created alpha signals for multiple frequencies across global indices in the USA, China, Europe, and UK, optimizing trading strategies for different market structures and liquidity conditions.
Senior Quantitative Research Associate
Wolfe Research, LLC
Dec 2020 – Jul 2024
- Engineered predictive alpha factors (Sharpe > 0.9) by applying advanced NLP (transformer models, knowledge graphs) to financial documents.
- Developed a machine learning-driven (LightGBM and Elastic Net ensemble), risk-neutralized factor model for loss-making companies, achieving a Sharpe Ratio of 1.53.
- Researched intangible assets as a systematic risk factor, constructing an enhanced book-to-market ratio.
- Led comprehensive exposure assessments on major macro and geopolitical risks.
- Led the design and deployment of scalable, high-performance dashboards for backtesting, stock screening, and strategy analysis.
Decision Analytics Associate Consultant
ZS
Jul 2017 – Jan 2020
- Led observational studies for Fortune 500 pharma clients using large EHR and Claims datasets on AWS Spark.
- Conducted survival analyses on NSCLC patients using Kaplan-Meier and Cox Proportional Hazard Model and summarized unstructured physician notes.
Skills & Technologies
Python
R
SQL
C++
NLP
Machine Learning
Backtesting
Attribution Analysis
Risk Management
Shiny
Education
Master of Financial Engineering (GPA: 3.925/4.0)
UCLA Anderson School of Management
Expected Dec 2025
B.Tech., Civil Engineering
Indian Institute of Technology Roorkee
Jun 2017
Certifications
- Applied Text Mining
- Convolutional Neural Network
- Neural Networks and Deep Neural Networks
- Applied Machine Learning
- Applied Social Network Analysis
- Paul Deitel’s Python Workshop