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
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Bachelor of Technology
Computational Mathematics
Grade: CGPA: 9.08
Work
Indian Institute of Technology, Guwahati
|Research Intern
Guwahati, Assam, India
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Summary
Conducted advanced research in quantitative finance, developing novel Deep Learning approaches for financial option pricing and market behavior analysis.
Highlights
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.
Achievements
Max 1252 Rated
Awarded By
Codeforces
Achieved a competitive programming rating of Max 1252 on Codeforces, demonstrating strong algorithmic problem-solving skills.
Solved 400+ Questions
Awarded By
LeetCode
Successfully solved over 400 algorithmic problems on LeetCode, showcasing proficiency in data structures and algorithms.
Certificates
Time Series Analysis and Forecasting with Python
Issued By
Not Specified
Google Advanced Data Analytics Specialization
Issued By
Positions of Responsibility
Data Science and Artificial Intelligence Club (DSAI), NIT-A
|Quantitative Finance Lead
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Summary
Led and organized quantitative finance projects within the Data Science and Artificial Intelligence Club at NIT-A.
Highlights
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