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ABOUT ME
With a Bachelor of Science in Mathematics and Computing from the Indian Institute of Technology Kharagpur, I developed a strong foundation in probability, statistics, linear algebra, time series, numerical analysis, and a broad range of other mathematical disciplines. Motivated by a strong interest in finance, I have a solid understanding of options pricing, risk management, trading algorithms, and corporate finance. Proficient in C++, Python, and MATLAB, I enjoy applying quantitative methods to real-world problems and am currently looking for a quantitative finance internship for Summer 2026
FEATURED POSTS
EDUCATION
Academic Background
Master of Financial Mathematics
North Carolina State University
Aug 2025 - Dec 2026
Bachelor of Science in Mathematics and Computing
Indian Institute of Technology Kharagpur
Aug 2021 - May 2025
Probability, Statistics & Stochastic Processes
• (MA20205) Probability and Statistics: Random variables and their distributions, Expectation and variance, Moments and cumulants, Joint and conditional distributions, Covariance and correlation, Moment‐generating and characteristic functions.
• (MA20208) Stochastic Processes and Applications: Markov chains (discrete and continuous‐time), Poisson and birth–death processes, Renewal theory, Stationarity and ergodicity, Brownian motion basics, Applications to queuing and reliability.
• (MA60280) Regression Analysis and Time Series Models: Simple and multiple linear regression, Least squares estimation, Hypothesis testing and model diagnostics, Autoregressive (AR), moving‐average (MA), and ARMA models, ARIMA forecasting, Seasonality and trend decomposition.
COURSEWORK INFORMATION
Numerical Methods & Computational Modelling
• (MA20201) Numerical Solution of Ordinary and PDE: Finite‐difference methods for ODEs (Euler, Runge-Kutta), Stability and error analysis, Finite‐difference schemes for elliptic, parabolic, and hyperbolic PDEs, Consistency and convergence.
• (MA20204) Applied Computational Methods: Interpolation and spline approximation, Numerical integration and quadrature, Eigenvalue problems (power method, QR), Numerical linear algebra (Gaussian elimination, LU/QR decomposition), Fast Fourier transform.
• (MA29202) Numerical Methods Laboratory: Implementation of ODE/PDE solvers in MATLAB/Python, Visualization of numerical errors, Stability experiments, Hands‑on with linear algebra routines.
• (MA30206) Mathematical Modelling: Formulation of mathematical models from real‐world problems, Dimensional analysis and nondimensionalization, Lumped‐parameter vs. distributed systems, Model validation and sensitivity analysis.
• (MA39206) Modelling and Simulation Lab: Building simulation models (discrete and continuous), Use of simulation software (e.g. Simulink), Monte Carlo simulation, Parameter estimation via simulation, Interpretation of simulation outputs.
Optimization & Algorithmic Design
• (MA30207) Design & Analysis of Algorithms: Algorithmic complexity (Big‑O, Ω, Θ), Divide‑and‑conquer, Greedy algorithms, Dynamic programming, Graph algorithms (shortest paths, spanning trees), NP‑completeness basics.
• (MA39203) Design & Analysis of Algorithms Lab: Implementation of classical algorithms in C/C++ or Python, Empirical time–space measurement, Use of profiling tools, Visualization of algorithm behavior.
• (MA30227) Optimization Techniques: Linear programming (simplex, duality), Integer programming formulations, Unconstrained optimization (gradient, Newton methods), Constrained optimization (Lagrange multipliers, Kuhn–Tucker conditions).
• (MA39207) Optimization Techniques Lab: Hands‑on with optimization solvers (e.g. CVX, PuLP), Modeling real problems as LP/IP/QP, Sensitivity and post‐optimality analysis.
• (MA60255) Computational Geometry: Convex hull algorithms (Graham scan, Jarvis march), Line‐segment intersection, Voronoi diagrams and Delaunay triangulations, Range searching and point‐location, Applications in graphics and GIS.
Machine Learning & Data Analysis
• (MA60274) AI & ML: Supervised learning (classification and regression trees, SVM), Unsupervised learning (k‑means, hierarchical clustering), Neural network fundamentals, Evaluation metrics (accuracy, precision/recall, ROC), Overfitting and regularization.
• (MA69202) AI & ML Laboratory: Programming classifiers and regressors in Python (scikit‑learn, TensorFlow/PyTorch), Data preprocessing and feature engineering, Model evaluation with cross‐validation, Hyperparameter tuning.
• (MA60306) Big Data Analysis: MapReduce paradigm, Hadoop and Spark basics, Data ingestion and ETL processes, Distributed algorithms for clustering and classification, Scalability and fault tolerance considerations.
• (MA69204) Statistics Software Lab: Use of R or Python for statistical analysis, Data visualization (ggplot2/matplotlib), Scripted workflows for reproducible research, Implementation of hypothesis tests and ANOVA, Generation of custom reports.
PROJECTS & INTERNSHIPS
Data Analyst Intern
Franklin Templeton Investments
May 2024 - Mar 2025
Project 1: Enhanced data accessibility for sales representatives via a Gen AI-powered chatbot application
• Conserved nearly 100+ man-hours by introducing Generative AI products in regular sales functions for US retail markets
• Enforced financial data privacy by conceptualizing SQL-GPT functionality, significantly lowering the risk of using LLMs
• Partitioned the database by sales territory to enforce role‑based access controls, restricting data visibility per region.
On Site
Hybrid
Project 2: Prototyped solutions leveraging social media, macroeconomic indicators, and sales‑activity notes to surface actionable sales insights
• Scanned 10k+ Twitter profiles of existing and potential clients to identify optimal product fits for each.
• Engineered a pipeline synthesizing macroeconomic signals from multiple news sources and internal newsletters to generate personalized talking points per client
• Analyzed 1k+ sales activity notes with advanced data techniques, scoring interactions to predict and prioritize follow‑up opportunities.
During my internship, I also maintained and enhanced monitoring solutions for authorized personnel to ensure strict compliance with the code of ethics; conducted preliminary research on multiple new product initiatives to inform development roadmaps, and honed my communication, organizational, coordination, and technical skills.
May 2024 - Mar 2025
May 2024 - Mar 2025
May 2024 - Mar 2025
May 2024 - Mar 2025
May 2024 - Mar 2025
May 2024 - Mar 2025
American Options in the Volterra Heston Model
Indian Institute of Technology Kharagpur
Sept 2024 - Apr 2025
Sept 2024 - Apr 2025
Autumn Semester: Studying rough volatility within the Volterra Heston framework to price American options
• Analyzed rough volatility by numerically solving stochastic differential equations derived from the Volterra Heston Model
• Developed and analyzed the convergence of Bermudan Options to American Options as the exercise dates are increased
• Engineered an open-source package in Python to efficiently run the Longstaff-Schwartz algorithm, helping in further research
Spring Semester: Enhanced the Volterra Heston model via bounded‑variance dynamics, jump‑clustering, and local‑volatility extensions.
• Introduced a Sandwiched Volterra Volatility process to enforce deterministic volatility bounds, preventing degenerate or explosive variance regimes.
• Implemented a rough Hawkes–Heston jump clustering extension to capture self‐exciting price and volatility jumps, enabling consistent SPX/VIX joint calibration.
• Integrated a local‐volatility leverage function to eliminate vanilla‐pricing errors and perfectly match market‐implied volatility surfaces.
Building Resilience through ESG
Indian Institute of Management Bangalore
Sept 2024 - Nov 2024
Objective: Evaluating the relationship between the financial stability of Indian PSUs and their compliance with ESG principles
• Conducted comprehensive ESG performance evaluation of Indian PSUs, aligning with national sustainability goals & SDGs
• Devised qualitative ESG evaluation metrics by leveraging machine learning techniques to analyze companies’ annual reports
• Analyzed financial stability during downturns by stress testing companies classified by low, moderate, & high ESG scores
• Provided comparative analysis on Indian PSUs’ governance resilience against global peers in various emerging markets
This research was presented at the 11th International Conference on Business Analytics and Intelligence held at the Indian Institute of Management Bangalore (Dec 2024)
SKILLS & EXPERTISE
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C++
Data Analysis
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Excel
SQL
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Python
Probability & Statistics
JEE Mains 2021
Ranked within the top 0.7% among nearly 1.1M candidates who appeared in Joint Entrance Examination Mains, 2021
ACHIEVEMENTS
JEE Advanced 2021
Ranked within the top 2% among nearly 200K candidates who qualified for Joint Entrance Examination Advanced, 2021
INSPIRE Scholarship Award
Awarded the INSPIRE Scholarship for pursuing a bachelor’s degree in pure sciences at one of the country’s best institutions
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