Devashish Mehta

CEO

New York City, New York, United States8 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in developing algorithmic trading strategies.
Strong background in statistical and machine learning techniques.
Proven ability to improve application performance in trading platforms.

Stackforce AI infers this person is a Fintech professional specializing in algorithmic trading and software development.

Contact

Skills

Core Skills

Algorithmic TradingMachine LearningSoftware DevelopmentApplication DevelopmentResearch

Other Skills

AlgorithmsCC++Deep LearningJavaJavaScriptLeadershipMultithreadingPortfolio constructionProbabilistic methodsPythonPython (Programming Language)React.jsStatistical methodsVert.x

About

Passionate about researching and developing systematic trading strategies for futures and equities. Interested in alpha generation and finding creative ways to generate high risk adjusted uncorrelated returns.

Experience

Hap capital

Quantitative Researcher

Jun 2022 – Present · 3 yrs 9 mos · New York, United States · On-site

Goldman sachs

3 roles

Associate

Dec 2021 – May 2022 · 5 mos

Analyst

Aug 2019 – Dec 2021 · 2 yrs 4 mos

Equities Trading Platform Strats, GSET

Summer Analyst, Securities Division

May 2018 – Jul 2018 · 2 mos · Bengaluru, Karnataka, India

Worked on the Electric Trading Platform to develop an end to end application for monitoring, admin overriding and viewing the trading phases of products evaluated using fids from market data (RMDS)
Worked with network datastreams and the firms transport layer to send/receive data b/w applications
Used latest frameworks/tools like Vert.x for the backend HTTP server and React.js for the frontend
Improved the performance of the application by using multithreading to support very fast data updates
Languages used: C++, Java, Python, JS and SLang

C++JavaPythonJavaScriptMultithreadingReact.js+3

Trexquant investment lp

Global Alpha Researcher

Nov 2017 – Aug 2019 · 1 yr 9 mos

Developed statistically-based medium-frequency equity strategies for algorithmic trading
Used statistical/probabilistic methods to design trading signals (alphas) and filtering alphas from a pool of over a million alphas
Used ML techniques and Markowitz MVO to assign weights to alphas for portfolio construction and optimisation
Implemented many different ideas for the strategy to make it ready for live trading

Statistical methodsProbabilistic methodsMachine LearningPortfolio constructionAlgorithmic trading

Indian institute of technology, kanpur

Summer Researcher

May 2017 – Aug 2017 · 3 mos · India

Worked on Deep Learning with Prof. Nisheeth Srivastava aiming to find how gestal visual priors are embedded in the state of the art deep learning models .

Deep LearningResearch