I am a Quantitative Developer with experience in designing and implementing high-performance trading systems, statistical models, and algorithmic trading strategies. With a strong foundation in financial engineering, computer science, and applied mathematics, I thrive at the intersection of technology and finance.

🎓 Education

• Master of Science in Financial Engineering, Stevens Institute of Technology (Ongoing, Dec 2025)
  Coursework: Market Microstructure, Algorithmic Trading Strategies, Quantitative Hedge Fund Strategies
• Master of Science in Computer Science, Georgia Tech (Ongoing, Dec 2025)
  Coursework: High-Performance Computing, Distributed Systems, Advanced Internet Computing Systems
• Master’s in Financial Engineering, WorldQuant University (2021-2024, 86%)
  Coursework: Financial Econometrics, Fixed Income, Portfolio Management, Risk Management
• B.Tech in Computer Science and Engineering, VIT, India (2014-2018, GPA: 8.78/10)

Mar 2023 – Jul 2024 | Mumbai, India

• Designed and implemented Map Construction and Routing Algorithms to solve complex NP-hard problems.
• Built a Large Language Model (LLM) for internal development and bug query resolution, reducing issue resolution time by 80%.
• Led a team of 12 to develop a high-performance geospatial mapping application using PostGIS, MongoDB, and AWS.

Feb 2022 – Oct 2022 | New York, USA

• Developed ML-driven Order and Execution Management Systems, improving trade execution efficiency by 20%.
• Backtested and deployed systematic merger arbitrage strategies, increasing alpha capture by 15%.
• Engineered risk-adjusted return models for optimizing portfolio risk exposure and factor analysis.
• Managed a combined AUM of $8.5 Billion across merger arbitrage and stock selection portfolios.

Jan 2020 – Jul 2021 | Chennai, India

• Migrated 1M+ lines of code to Python 3.8, improving efficiency by 80%.
• Developed trading services for bonds, futures, and options within the FICC post-trade processing team.
• Reduced trade processing latency by 50% through Python and C++ integration on the QUARTZ platform.

• Dynamic Portfolio Optimization (Master's Thesis):
  Leveraged stochastic calculus for real-time portfolio risk mitigation and adjustment.

• Financial Modeling Using Stochastic Calculus:
  Applied advanced models (e.g., GBM, Ito’s Lemma, Mean-Reverting Processes) for option pricing and derivative strategies.

• Real-Time Market Anomaly Detection:
  Developed low-latency algorithms for HFT applications using advanced signal processing and optimization techniques.

• Advanced Derivatives Modeling:
  Implemented Monte Carlo, SABR, Heston, and Hull-White models for derivative pricing and robust risk management.

• Derivative Pricing Models: Black-Scholes, Heston, SABR, Hull-White, Monte Carlo Simulation
• Portfolio Management: Risk Management, Factor Modeling, Dynamic Optimization
• Statistical Techniques: Time Series Analysis, Statistical Arbitrage, Risk-Adjusted Return Modeling

• Stochastic Calculus: Brownian Motion, Geometric Brownian Motion, Ito’s Lemma
• Numerical Methods: PDEs, ODEs, Mean-Reverting Processes (Ornstein-Uhlenbeck)
• Optimization: Linear and Non-Linear Optimization

• Strong leadership and team management experience (Led teams of up to 12).
• Proficient in collaborative agile development methodologies.
• Skilled at breaking down complex problems and delivering scalable solutions.

Here’s the full-fledged Certifications section, formatted with attractive badges and clickable links for easy navigation:

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• Financial Engineering and Risk Management - Part I & II (Coursera)
• Investment Foundations Program (CFA Institute)
• The Complete Financial Analyst Training & Investing Course
• Machine Learning for Trading Specialization (Google Cloud)
• Trading Strategies in Emerging Markets Specialization (ISB)
• Finance & Quantitative Modeling for Analysts (University of Pennsylvania, Wharton)

• Algorithmic Trading Specialization (ISB)
  • Includes: Advanced Trading Algorithms, Portfolio Design, and Trading Basics
• Investment Management Specialization (University of Geneva, UBS)
• Corporate Finance and Valuation (NYU Stern - Aswath Damodaran)

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• Applied Data Science with Python Specialization (University of Michigan)
  • Includes: Applied Text Mining, Machine Learning, and Data Visualization
• Data Science Foundations using R Specialization (Johns Hopkins University)
• Big Data Specialization (UC San Diego)

• Data Structures and Algorithms Specialization (Coursera)
• Algorithms Part I & II (Princeton University)
• Big Data - Capstone Project
• Machine Learning with Big Data

• Regression Models (Data Science Statistics and Machine Learning Specialization)
• Exploratory Data Analysis
• Practical Machine Learning (JHU)
• Python for Everybody (University of Michigan)

You can show support by starring my repos, liking and sharing my videos, and subscribing to my channel.

If you really, really, really enjoy my work, you can also support me on Patreon.

Thank you all so much 🙏