--- title: "Home" description: "Profile, experience, research, projects, skills, education, GitHub activity, and writing" url: "https://www.shreejitverma.com" author: "Shreejit Verma" --- Senior Quantitative Developer at Barclays · New York, NY # Shreejit Verma Quantitative Developer & Researcher Quantitative Developer, Quantitative Researcher, and Quantitative Trading Engineer based in New York. I build low-latency **C++ trading and risk systems**: FRTB market risk engines at **Barclays**, automated market making at **BNP Paribas**, and an **FPGA and kernel-bypass** market-making system for my MS thesis, plus statistical arbitrage and ML-driven alpha research. [View Resume](https://www.shreejitverma.com/resume) · [Download PDF](https://www.shreejitverma.com/Shreejit_Verma_Resume.pdf) · [Book a Call](https://calendly.com/shreejitverma) [View Experience ](https://www.shreejitverma.com/#experience) · [Key Projects ](https://www.shreejitverma.com/#projects) · [shreejitverma@gmail.com](mailto:shreejitverma@gmail.com) ![Shreejit Verma](https://www.shreejitverma.com/images/profile-square.jpg) - $500M daily market-making volume C++ automated market-making stack, BNP Paribas CIB - $8.5B AUM merger-arbitrage book Systematic strategies, Versor Investments - 50% lower trade processing latency C++ trade pipelines, Bank of America FICC - +20% higher Sharpe ratio Regime-based C++ execution framework, backtested ## Professional Experience ### [Barclays](https://www.ib.barclays/) Oct 2026 – Present Senior Quantitative Developer (Contract), FRTB Market Risk | New York, USA (Hybrid) - Architecting low-latency C++ and Python distributed pricing and risk calculation pipelines, optimizing Expected Shortfall (ES), Default Risk Charge (DRC), and Non-Modellable Risk Factor (NMRF) simulations across multi-asset trading desks. - Engineering high-throughput aggregation engines for the Sensitivities-Based Method (SBM), Gross Jump-to-Default (JTD), and Residual Risk Add-on (RRAO). - Designing automated backtesting and P&L Attribution (PLA) test suites (Risk-Theoretical vs. Hypothetical P&L), establishing stable model eligibility pipelines and minimizing capital charge penalties across major trading desks. - Scaling real-time scenario generation and risk factor time-series pipelines across high-performance grid environments, integrating kdb+/q and distributed message queues to ingest multi-terabyte tick and pricing feeds for risk factor observability. - Partnering with Quantitative Research, Front Office Trading, Risk Methodology, and Model Risk Governance to implement, validate, and document Basel IV compliance frameworks for regulatory audits (Fed, PRA, FINMA). ### [BNP Paribas CIB](https://cib.bnpparibas/) Feb 2026 – May 2026 C++ Quantitative Developer (Co-op), Automated Market Making | New York, USA - Built low-latency components of the automated market-making stack for the Prime Credit Market (average $500M of daily market-making volume), spanning real-time market-data ingestion, tick analytics, and pricing/execution paths. - Profiled and optimized the software hot path feeding FPGA-accelerated market-data handlers and quoting engines. - Integrated secure on-premise LLM tooling with Git/Jira/Confluence to automate code, testing, and documentation workflows. ### [LogiNext Solutions Inc.](https://loginextsolutions.com/) Mar 2023 – Jul 2024 Senior Software Engineer, Analytics | Mumbai, India - Architected Map Construction, Map Routing, and Rich Vehicle Routing algorithms (3 nested NP-Hard problems) using CP-SAT constraint programming and convex optimization over PostGIS, MongoDB, and S3. - Led a 12-engineer team delivering a high-throughput geospatial mapping application platform. - Built an LLM-powered debugging and query-resolution tool used company-wide, cutting mean bug-resolution time by 80%. ### [Versor Investments (QR Systems LLP)](https://versorinvest.com/) Feb 2022 – Oct 2022 Quantitative Developer, Merger Arbitrage and Stock Selection Portfolio | Mumbai, India - Developed and backtested systematic merger-arbitrage strategies for an $8.5 Billion AUM fund, improving alpha capture by 15%. - Built and deployed ML pipelines for Order and Execution Management Systems, increasing trade execution efficiency by 29%. - Designed an ESG-driven merger-arbitrage signal from pre- and post-merger statistics, later run as a standalone portfolio and embedded across existing portfolios. ### [Bank of America](https://www.bankofamerica.com/) Jan 2020 – Jul 2021 Senior Software Engineer, Fixed Income Commodities and Currencies (FICC) | Chennai, India - Engineered Python-based trading services enhancing storage, processing, matching, and execution of trades on QUARTZ. - Integrated C++ pipelines to store trades in the object-oriented database SANDRA, reducing trade processing latency by 50%. - Led the migration of 1 million+ lines of code to Python 3.8, enhancing scalability and execution efficiency by 40%. ### [Bank of America](https://www.bankofamerica.com/) Jun 2018 – Dec 2019 Senior Tech Associate, Data Analysis and Insight Technology | Chennai, India - Architected and developed an ML/AI platform to deploy predictive models, increasing decision-making accuracy by 67%. - Designed machine learning models for data validation rules prediction, reducing workload by close to 36 Full-Time Equivalents (FTEs). ## Research Thesis work and research systems, each with source code or a live tool. Featured case study ### [Trishul: AI-Integrated FPGA for Market Making](https://www.shreejitverma.com/work/trishul) MS Thesis, Stevens Institute of Technology Oct 2025 – May 2026 Sub-10us hardware-software co-designed market-making system: Verilog ITCH 5.0 parsing, L2 book, fixed-point RL inference, and single-cycle pre-trade risk on the FPGA critical path, with a zero-allocation C++20 control plane using lock-free SPSC queues and kernel-bypass style polling. C++20 · Verilog · FPGA · Kernel Bypass · Limit Order Book · RL [Read the case study ](https://www.shreejitverma.com/work/trishul) · [Source code](https://github.com/shreejitverma/trishul-ultra-hft-project) ### [Dynamic Portfolio Optimization](https://github.com/shreejitverma/Dynamic-Portfolio-Optimization) MS Thesis, WorldQuant University · Mar 2024 – Jun 2024 Real-time portfolio optimization with convex and non-convex methods, adaptive rebalancing, and multi-factor modeling across interest rate, FX, credit, and market risks. Portfolio Optimization · CVXPY · Factor Models ### [Value Intelligence Platform](https://www.shreejitverma.com/value-investing) Live Research tool · runs on this site Reproducible value-investing screen: a deterministic multi-factor scoring engine with published formulas, weights, and limitations, golden-value tests, and CSV export. [Open the platform ](https://www.shreejitverma.com/value-investing) ## Key Projects Execution, alpha research, and engineering projects. Cards with a GitHub icon link to the source. ### [Adaptive Volatility Regime-Based Execution and Risk Framework](https://github.com/shreejitverma/Adaptive-Volatility-Regime-Based-Execution-and-Risk-Framework) C++ library · Sept 2025 – Dec 2025 Regime-switching execution framework selecting among passive, TWAP, and aggressive execution using microstructure-robust volatility estimators, a Gaussian HMM, and Hawkes-process liquidity stress detection: +20.0% Sharpe Ratio, -6.1% transaction costs, -20.1% CVaR. C++17 · Execution Algorithms · HMM · Risk ### [Statistical Arbitrage Reversal and Momentum Strategies](https://github.com/shreejitverma/Statistical-Arbitrage-Reversal-and-Momentum-Strategies) Quant Researcher, WallStreetQuants · Jun 2025 – Aug 2025 120-day volume-momentum crypto portfolio strategy: 155.76% annualized return and 1.94 Sharpe Ratio post transaction costs, outperforming the Bitcoin buy-and-hold benchmark. Python · Backtesting · Alpha Research ### [CryoZen: Sovereign AI Command Center](https://github.com/shreejitverma/srijan) Independent project · May 2026 – Present Self-hosted, local-first AI workspace orchestrating LLM providers behind a unified API, with MCP tool-calling agents, RAG and persistent semantic memory, and hardware-aware deployment of quantized open-weight models; nothing leaves the host by default. LLM Infrastructure · MCP · RAG · Agents ### [Plug-and-Play Agentic AI Engineering Harness](https://github.com/shreejitverma/dotfiles-nix) Independent project · May 2026 – Present Cross-platform agentic developer platform on NixOS with declarative configuration, multi-agent orchestration, isolated Git worktrees, autonomous task execution, and CI-gated shipping. NixOS · Multi-Agent Systems · DevEx ### ESG Merger Arbitrage Strategy Versor Investments · Apr 2022 – Jun 2022 ESG-driven merger-arbitrage strategy capturing the opportunity created by ESG scores on target and acquirer pre- and post-merger statistics; converted into a standalone portfolio and embedded across all existing portfolios. ESG · Merger Arbitrage · Portfolio Strategy ### Financial Modelling using Stochastic Calculus Modeled asset prices and derivative strategies with Brownian motion, GBM, Ito's Lemma, martingales, Girsanov's theorem, SDEs, and the Fokker-Planck and Kolmogorov equations for volatility and interest rates. Stochastic Calculus · Derivatives Pricing · Python ### Blockchain in Retail Jan 2018 – Mar 2018 Decentralized e-commerce platform securing and streamlining retail transactions with smart contracts, currency conversion, custom hashing, and matching algorithms. Blockchain · Smart Contracts · Solidity ### QS Rank Predictor Jun 2017 – Jul 2017 Ensemble of deep neural networks predicting QS World University Rankings, with suggestions on the areas each institution should improve. Deep Learning · Neural Networks · Predictive Modeling ## Technical Arsenal ### Low-Latency Systems - C++20/23 - Lock-free data structures - Memory pools - SIMD - Cache-aware design - DPDK / kernel bypass - FPGA (Verilog, VHDL) - TCP/IP, UDP multicast - Linux kernel and performance tuning ### Programming Languages - C++ - Python - C - Java - R - MATLAB - kdb+/q - OCaml - JavaScript / TypeScript - Verilog - VHDL - Bash ### Quantitative Finance - Market microstructure - Market making - Execution algorithms - Statistical arbitrage - Derivatives pricing - Greeks - Factor modeling - Portfolio optimization - Risk management ### Market Risk - FRTB (IMA / SA) - Basel IV - Expected Shortfall - DRC / NMRF - Sensitivities-Based Method - P&L Attribution - Backtesting ### Mathematics & Statistics - Stochastic calculus - Probability - PDEs - Linear algebra - Markov chains - Time series analysis - Bayesian statistics - Numerical methods - Differential equations ### Machine Learning & AI - PyTorch - TensorFlow - scikit-learn - XGBoost - Random forests - RNN / LSTM - Reinforcement learning - Clustering - NLP - LLMs, RAG, MCP agents ### Data & Distributed Compute - NumPy, SciPy, Polars, pandas - Spark / PySpark - Dask - Hadoop - Kafka - ZeroMQ - Airflow - PostgreSQL - MongoDB - Cassandra - Redis - InfluxDB - SQL / BQL - FastAPI, REST APIs - Slurm - IBM Symphony ### Systems & DevOps - Docker - Kubernetes / OpenShift - AWS - GCP - Serverless - CMake - Git - Jenkins - Ansible - CI/CD - Linux ## Engineering Philosophy The principles behind the systems above, each tied to where it was applied. - ### Ultra-Low Latency Minimizing microsecond-level overhead through kernel bypass (DPDK) and FPGA acceleration. [In practice: Trishul puts parsing, the book, inference, and risk on the FPGA critical path](https://www.shreejitverma.com/work/trishul) - ### Deterministic Execution Predictable response times via lock-free data structures, pre-allocated memory, and cache-line alignment. [In practice: Zero-allocation C++20 control plane with lock-free SPSC queues](https://www.shreejitverma.com/work/trishul) - ### Alpha-Centric Design Translating quantitative signals into execution strategies with minimal slippage and transaction cost. [In practice: Merger-arbitrage strategies for an $8.5B AUM fund at Versor](https://www.shreejitverma.com/#experience) - ### Scalable Architecture Modular systems that handle millions of events per second and degrade gracefully under load. [In practice: FRTB risk pipelines on high-performance grids at Barclays](https://www.shreejitverma.com/#experience) - ### Hardware Synergies Software shaped for modern CPUs (SIMD, branch prediction, cache hierarchy) and custom hardware. [In practice: Hot path feeding FPGA market-data handlers at BNP Paribas](https://www.shreejitverma.com/#experience) - ### Statistical Rigor Rigorous backtesting and risk modeling so performance holds across market regimes. [In practice: Regime-switching execution framework with HMM and Hawkes models](https://www.shreejitverma.com/#projects) ## Education ### Georgia Institute of Technology (Online) Aug 2024 – Expected Dec 2026 M.S. in Computer Science, Specialization in Computing Systems Coursework: Computer Networks, Advanced Operating Systems, Distributed Computing, Database Management Systems. ### Stevens Institute of Technology Aug 2024 – May 2026 M.S. in Financial Engineering GPA 3.974/4.0 Coursework: Market Microstructure, Portfolio Theory and Applications, Algorithmic Trading Strategies, Multivariate Statistics. ### WorldQuant University Dec 2021 – May 2024 M.S. in Financial Engineering GPA 86% Coursework: Deep Learning for Finance, Financial Econometrics, Fixed Income, Equity, Portfolio Management, Risk Management. ### Carnegie Mellon University, Tepper School of Business Aug 2021 – Oct 2021 M.S. in Computational Finance (program withdrawn due to father’s illness) Coursework: Investments, Statistical Machine Learning, Simulation Methods, Financial Computing, Algorithmic Optimization. ### Vellore Institute of Technology Jul 2014 – Sept 2018 B.Tech in Computer Science and Engineering GPA 8.78/10.0 Coursework: Data Structures and Algorithms, Programming Language Translators, Natural Language Processing. ## GitHub Impact Activity across public and private repositories, refreshed daily from the GitHub API. [View the GitHub profile](https://github.com/shreejitverma). - 2,724 contributions in the last year Across public and private repositories - 2,461 commits in the last year 195 pull requests and 7 issues opened - 189 pull requests merged 2 open, 5 closed without merge - 0d current contribution streak Longest in the last year: 9 days - 29 repositories committed to 66 public repositories, 192 stars, 89 forks - 2017 on GitHub since 88 followers From the GitHub API, updated October 15, 2026. Contribution counts include private repositories. ### Languages Share of commits in the last 12 months, by language · · · · · · · · - Python · 53.2% - JavaScript · 24.4% - C++ · 11.7% - TypeScript · 6.1% - Shell · 1.9% - Java · 1.0% - C · 0.4% - Verilog · 0.3% - Other · 0.9% Each repository's commits are split by its language mix; notebooks count as Python and markup is excluded. ![Contribution streak: total contributions, current streak, and longest streak](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/streak.light.svg)![Contribution streak: total contributions, current streak, and longest streak](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/streak.dark.svg) ![Contribution calendar, commit streaks, and pull request status](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/metrics.calendar.svg) ![3D contribution calendar for the last year](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/contrib3d.green-animate.svg)![3D contribution calendar for the last year](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/contrib3d.night-green.svg) ![Animated snake eating the contribution graph](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/snake.light.svg)![Animated snake eating the contribution graph](https://raw.githubusercontent.com/shreejitverma/shreejitverma/output/snake.dark.svg) ![Profile visitor count](https://visitor-badge.laobi.icu/badge?page_id=shreejitverma) ## Writing October 9, 2026 · 11 min read ### [FRTB for Engineers: What a Market Risk Capital Engine Actually Computes](https://www.shreejitverma.com/writing/frtb-for-engineers) A systems view of the Fundamental Review of the Trading Book: Expected Shortfall with liquidity horizons, NMRF stress scenarios, the Default Risk Charge, the Sensitivities-Based Method, and the PLA and backtesting tests that decide whether a desk may use its internal model. [Read the article ](https://www.shreejitverma.com/writing/frtb-for-engineers) ## Awards & Leadership ### Awards - **1st Place, Vanguard ETF Trading Challenge** · \- Personal portfolio; 6th place for the team portfolio. - **Global Recognition Gold Award, Bank of America** · \- Led an enterprise-wide AI/ML campaign identifying 64 high-impact use cases; delivered AI/ML lectures to 2500+ employees across 4 events. - **Global Recognition Silver Award, Bank of America (2x)** · \- Total Return Swap post-trade processing contributions and an end-to-end in-house AI/ML framework. - **President, Stevens Graduate Financial Association** · \- Led the graduate finance student organization at Stevens. - **Beta Gamma Sigma** · \- International business honor society. - **State Rank Holder** · \- International Science Olympiad and International Mathematics Olympiad. ### Interests & Languages #### Interests Chess, Poker, F1, Martial Arts, Cricket, Boxing, Badminton, Reading, Cooking, Dancing, Psychology, History, Philosophy #### Languages Fluent English, Hindi Intermediate French, Sanskrit, Spanish, Russian Beginner Chinese, Italian, Tamil, Punjabi ## Certifications ### Finance - [CFA Level 1](http://basno.com/l2c3uqav) - [Bloomberg Market Concepts (BMC)](https://portal.bloombergforeducation.com/certificates/8Nm9y3yx5b9yaWztgxSmewLD) - [Financial Engineering and Risk Management Part I & II (Columbia)](https://coursera.org/share/70b94743c090c143954cdcbe01ebf521) - [Investment Foundations Program (CFA Institute)](http://basno.com/cfbvwwwf) - [Machine Learning for Trading Specialization (Google Cloud / NYIF)](https://coursera.org/share/7a85fee31445a626d1212f7c2f55eeab) - [Investment Management Specialization (Geneva / UBS)](https://www.coursera.org/specializations/investment-management) - [Trading Strategies in Emerging Markets (ISB)](https://www.coursera.org/specializations/trading-strategy#courses) - [Finance & Quantitative Modeling for Analysts (Wharton)](https://coursera.org/share/abe2916c68432d5d156494c2f1f59b6d) - [Corporate Finance and Valuation (NYU Stern, Aswath Damodaran)](https://coursera.org/share/ad6c6e3574db71e2e38777b74b6af97f) - [The Complete Financial Analyst Training & Investing Course](https://www.udemy.com/course/the-complete-financial-analyst-training-and-investing-course/) ### Computer Science - [Deep Learning Specialization (Andrew Ng)](https://coursera.org/share/62c6f8a2d4a998dc4856249a1a937e17) - [Algorithms, Part I & II (Princeton)](https://www.coursera.org/learn/algorithms-part1) - [Data Structures and Algorithms Specialization](https://coursera.org/share/98a957a6518b5ca605f44f365df05151) - [Applied Data Science with Python (Michigan)](https://coursera.org/share/a24e1310f62486c32f6a2393fa1240dc) - [Data Science Statistics and Machine Learning (Johns Hopkins)](https://www.coursera.org/specializations/data-science-statistics-machine-learning) - [Data Science Foundations using R (Johns Hopkins)](https://coursera.org/share/3ca9e040262f60d9c367379013a1e7c1) - [Big Data Specialization (UC San Diego)](https://coursera.org/share/e3c471b726d96029d683efcfec957692) ## Essential Reading A curated library of the books that shaped my trading philosophy and technical approach, from stochastic calculus to Eastern philosophy. 2,890 books across 10 shelves - Finance & Trading 774 - Self-Help & Psychology 500 - Computer Science & Data 310 - Science & Math 281 - History & Geopolitics 275 - Business & Leadership 260 - Philosophy & Spirituality 198 - Fiction & Literature 146 - Education & Reference 85 - General 61 [View Full Reading List ](https://www.shreejitverma.com/books) - ![Encyclopedia of Chart Patterns cover](https://www.shreejitverma.com/books/51lKgRQh1XL._SX346_BO1204203200_.jpg.webp) Encyclopedia of Chart Patterns Thomas N. Bulkowski - ![Trading in the Zone cover](https://www.shreejitverma.com/books/51pJPs1sMHL._SX320_BO1204203200_.jpg.webp) Trading in the Zone Mark Douglas - ![The Intelligent Investor cover](https://www.shreejitverma.com/books/51DLoxAJ68L._SX324_BO1204203200_.jpg.webp) The Intelligent Investor Benjamin Graham - ![Technical Analysis from A to Z cover](https://www.shreejitverma.com/books/0071363483.01._SCLZZZZZZZ_SX500_.jpg) Technical Analysis from A to Z Steven B. Achelis - ![Super Trader cover](https://www.shreejitverma.com/books/51zIH54q13L._SX346_BO1204203200_.jpg.webp) Super Trader Van K. Tharp - ![High Probability Trading cover](https://www.shreejitverma.com/books/51rC1PZVJjL._SX328_BO1204203200_.jpg.webp) High Probability Trading Marcel Link - ![Options, Futures, and Other Derivatives cover](https://www.shreejitverma.com/covers/options-futures-and-other-derivatives-8aaef618bc.webp) Options, Futures, and Other Derivatives John C. Hull - ![Stochastic Calculus for Finance II cover](https://www.shreejitverma.com/covers/stochastic-calculus-models-for-finance-ii-continuous-time-mo-e61ea199a1.webp) Stochastic Calculus for Finance II Steven E. Shreve - ![The Man Who Solved the Market cover](https://www.shreejitverma.com/covers/the-man-who-solved-the-market-how-jim-simons-launched-the-qu-896905a817.webp) The Man Who Solved the Market Gregory Zuckerman - ![Machine Learning for Asset Managers cover](https://www.shreejitverma.com/covers/machine-learning-for-asset-managers-1c342c7280.webp) Machine Learning for Asset Managers Marcos López de Prado - ![A Practical Guide to Quantitative Finance Interviews cover](https://www.shreejitverma.com/covers/a-practical-guide-to-quantitative-finance-interviews-bed0e3f4df.webp) A Practical Guide to Quantitative Finance Interviews Xinfeng Zhou - ![Fooled by Randomness cover](https://www.shreejitverma.com/covers/fooled-by-randomness-the-hidden-role-of-chance-in-life-and-i-f61c3aac84.webp) Fooled by Randomness Nassim Nicholas Taleb