ADARSH KUMAR BANTH

Chandigarh

Summary

Worked as a Quantitative Research Analyst with expertise in data analysis, trading strategies, and financial modeling. Proficient in Python, C++, SQL, and software tools, with experience in algorithmic trading. Knowledgeable in system design, databases, networks and financial derivatives. Passionate about coding, software systems, markets, derivatives, and trading strategies

Work History

Quantitative Research Analyst

Greenland Investment Management

10 2022 - 07 2023

Conducted fundamental arbitrage research on Soybean commodities, analyzing fair value and spread calculations for futures trading on CME and DCE exchanges.
Interpreted signals from Soybean spreads, fair values, and fundamental price and volume data; backtested trading strategies based on these signals.
Calculated interest rates for various commodity contracts, supporting daily trading operations.
Developed a trade monitoring system to track filled trades, prices, and volumes across exchanges, enabling daily PnL calculations.
Optimized Excel VBA code performance, streamlining daily trading and operational processes.
Managed daily data download and processing, ensuring seamless monitoring and troubleshooting.

Software Engineering Intern

Societe Generale GSC

05 2021 - 07 2021

Developed Resumeasy, an ML+NLP-driven application to automate candidate selection by ranking resumes and generating brief summaries.
Built a Named Entity Recognition (NER) model using spaCy to extract key candidate details like name, email, education, experience, and skills.
Implemented a FastAPI-based backend for seamless integration with the application interface.
Designed a dynamic compatibility scoring system, allowing recruiters to weight skills and evaluate candidates effectively.

Education

B.Tech - Electrical Engineering

Indian Institute of Technology

01.2022

Skills

C, C, Python, R, HTML
MySQL, MongoDB, PostgreSQL, Redis
Matlab, Git, SVN, Excel

Pandas, MatPlotLib, SpaCy, Scikit-learn, Standard Template Library (STL)
Multivariate analysis
Quantitative research

Projects

Audio Detection and Classification (Sep’20 - Dec’20 )

Course Project Instructor: Dr. Vipul Arora, Dept. Of Electrical Engg., IIT Kanpur

Worked on detection of Single & Multiple events in their temporal sequence in an audio file using weakly labelled datasets
Used spectrograms as features along with implementing Convolutional neural network (CNN) for single event detection
Identified features to be extracted for the classifier and trained the model on a dataset resulting in a test accuracy of 59%

Scholastic Achievements

Secured All India Rank 600 in JEE Advanced 2018
Secured All India Rank 372 in JEE Mains 2018
Qualified for Kishore Vaigyanik Protsahan Yojana fellowship 2017 with AIR 975
Qualified for Indian National Mathematics Olympiad 2016 with Regional rank 10 in RMO, 2016.
Active member of Codechef and Codeforces with max ratings of 1874 and 1645 respectively.

Coursework

Fundamentals of Computing
Introduction to Mathematical Economics
Probability and Statistics
Financial Engineering
Data Structures & Algorithms
Real Analysis & Multivariable Calculus
Linear Algebra & ODE
Macroeconomics-I
Statistical Simulation and Advanced Statistical methods
Machine Learning for Data Analysis
Signal Processing
Microeconomics

Timeline