Hi 
I'm, Shreejit
👩💻 About Me
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)
🏢 Professional Experience
LogiNext Solutions Inc. — Senior Software Engineer (Head of Analytics)
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.
Versor Investments (QR Systems LLP) — Quantitative Developer
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.
Bank of America (BA Continuum) — Senior Software Engineer
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.
🚀 Key Projects
- 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.
🛠 Skills
Programming Languages
- Python, C++, Java, R, SQL, JavaScript, Node.js, MATLAB, KDB+/Q, OCaml, Bash
Technologies and Frameworks
- TensorFlow, Scikit-learn, React, PostgreSQL, Hadoop, Spark, Airflow, Docker, Redis, Kubernetes, AWS
Quantitative Finance
- 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
