Yogesh Gupta

Product Engineer

South Delhi, Delhi, India5 yrs 11 mos experience

Most Likely To Switch

Key Highlights

Graduated from IIT Delhi with a Dual Degree in Mathematics and Computing.
Experience in quantitative research and data science roles.
Proficient in multiple programming languages and machine learning techniques.

Stackforce AI infers this person is a Quantitative Researcher with expertise in Financial Markets and Data Science.

Contact

yogesh.gupta@gravitontrading.com +919013646171 LinkedIn

Skills

Core Skills

Financial MarketsMarket AnalysisAlgorithm DesignData MiningMachine Learning

Other Skills

Algorithm AnalysisAlgorithmsCC++DBSCANData ScienceData StructuresDeep LearningElectronic Trading SystemsGame TheoryJavaKerasLinear AlgebraLinuxMarket Data

About

Quant Researcher graduated in Mathematics and Computing from IIT Delhi. I can be reached at yogesh.gupta@iitdalumni.com

Experience

Graviton research capital llp

Quantitative Researcher

Jun 2024 – Present · 1 yr 10 mos · Gurugram, Haryana, India

Worldquant

Senior Data Scientist

Jun 2021 – May 2024 · 2 yrs 11 mos · New Delhi, Delhi, India

Alphagrep securities

Quantitative Researcher

Jul 2020 – Jun 2021 · 11 mos · Gurugram, Haryana, India

Financial MarketsMarket AnalysisMarket DataElectronic Trading Systems

Bidgely

Data Science Internship

May 2019 – Jul 2019 · 2 mos · Bengaluru Area, India

Facebook

Software Engineer Internship

Jan 2019 – Mar 2019 · 2 mos · London, United Kingdom

Adobe

Machine Learning Research Internship at Adobe

May 2018 – Jul 2018 · 2 mos · Noida Area, India

Worked on Topological Data Analysis and it's Applications to Deep Learning.

Worldquant university

Introduction to Data Science Module

Mar 2018 – Jun 2018 · 3 mos

Completed a module on introduction to Data Science with honors.
https://wqu-cert.thedataincubator.com/certificate?key=8118356928801688257

Prokure

Software Developer Internship

May 2017 – Jul 2017 · 2 mos · Hauz Khas New Delhi

Vehicle Routing Problem
Implemented a centroid based heuristic algorithm for capacitated vehicle routing problem in python. The routes were further optimised based on the time and distance values extracted from google's distance matrix api.
DBSCAN
Implemented DBSCAN algorithm to filter out noise points from the real time data of a biker using speed and acceleration.This led to an accurate estimate of the total distance travelled.
Collaborative filtering
Implemented Collaborative Filtering for Implicit Feedback Datasets to give product recommendations to the users.