# Pratyush Baliarsingh - Aspiring Quantitative Finance & Deep Learning Engineer
Source: https://hello.cv/pratyushbaliarsingh
Mumbai

## Links
- LinkedIn | https://www.linkedin.com/in/pratyush-baliarsingh
- GitHub | https://github.com/pratycodes

## About
Highly analytical Computational Mathematics student with a strong foundation in Deep Learning, Quantitative Finance, and AI/ML. Proven ability to develop advanced models for financial markets, optimize portfolios, and detect anomalies, as demonstrated by achieving a +2.6% better return than S&P 500 and improving model accuracy by 20%. Seeking to leverage expertise in data science, algorithmic trading, and financial modeling to drive impactful solutions in a dynamic quantitative role.

## Education
### National Institute of Technology, Agartala | Computational Mathematics
CGPA: 9.08

## Work
### Research Intern | Indian Institute of Technology, Guwahati
Conducted advanced research in quantitative finance, developing novel Deep Learning approaches for financial option pricing and market behavior analysis.
- Researched and developed novel Deep Learning models for pricing vanilla and exotic financial options under the guidance of Professor N. Selvaraju.
- Engineered, trained, and evaluated complex neural architectures to accurately capture path-dependent and non-linear payoffs, alongside volatility behavior in financial markets.
- Benchmarked Deep Learning models against classical financial models, including Black-Scholes-Merton (BSM), Heston, SABR, Longstaff-Schwartz, and Monte Carlo Simulations.
- Co-authored a research paper based on this work, currently under peer review, contributing to cutting-edge financial research.

## Projects
### Fintrix - Reinforcement Learning-Based Portfolio Optimization Framework
https://github.com/pratycodes/Fintrix
Developed a full-stack reinforcement learning system for universal market portfolio optimization.
### Anomaly Detection in Stock Prices Using an LSTM Autoencoder
https://github.com/pratycodes/Stock-Sentry
Implemented an LSTM Autoencoder for monitoring stock price data and identifying anomalies.

## Achievements
### Max 1252 Rated
Codeforces
Achieved a competitive programming rating of Max 1252 on Codeforces, demonstrating strong algorithmic problem-solving skills.
### Solved 400+ Questions
LeetCode
Successfully solved over 400 algorithmic problems on LeetCode, showcasing proficiency in data structures and algorithms.

## Certificates
### Time Series Analysis and Forecasting with Python
Not Specified | 2025-04-01
### Google Advanced Data Analytics Specialization
Google | 2023-10-01

## Positions of Responsibility
### Quantitative Finance Lead | Data Science and Artificial Intelligence Club (DSAI), NIT-A
Led and organized quantitative finance projects within the Data Science and Artificial Intelligence Club at NIT-A.
- Spearheaded the development and execution of several quantitative finance projects, fostering member engagement and skill development within the club.

## Skills
### Programming Languages
- C++
- Python
- Rust
- R
- SQL
### Data Science & ML Libraries
- NumPy
- Pandas
- Matplotlib
- Seaborn
- scikit-learn
- TensorFlow
- PyTorch
- Ray
- Gymnasium
- Amazon Chronos
- QuantLib
### Computer Science Fundamentals
- Data Structures and Algorithms (DSA)
- Object-Oriented Programming (OOPS)
- Database Management Systems
### Development Tools
- Git
- GitHub
- MATLAB
- VSCode
- Jupyter Notebooks

## Languages
- English | Fluent
- Hindi | Native
- German | Conversational

## Source
Read this profile on Hello.cv: https://hello.cv/pratyushbaliarsingh
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