# Shreejit Verma

> Quantitative Developer, Quantitative Researcher, and Quantitative Trading Engineer based in New York, NY. Specializes in FRTB and Basel IV market risk engines, C++ low-latency automated market making, FPGA/DPDK sub-10 microsecond trading systems, statistical arbitrage, merger arbitrage, and machine-learning-driven alpha research for hedge funds, proprietary trading firms, and high frequency trading firms.

Current role: Senior Quantitative Developer (Contract), FRTB Market Risk at Barclays, New York, USA (Hybrid) (Oct 2026 - Present).
Previous role: C++ Quantitative Developer (Co-op), Automated Market Making at BNP Paribas CIB, New York, USA (Feb 2026 - May 2026).
Education: M.S. in Computer Science, Specialization in Computing Systems, Georgia Institute of Technology (Online) (Aug 2024 - Expected Dec 2026); M.S. in Financial Engineering, Stevens Institute of Technology (Aug 2024 - May 2026); M.S. in Financial Engineering, WorldQuant University (Dec 2021 - May 2024); B.Tech in Computer Science and Engineering, Vellore Institute of Technology (Jul 2014 - Sept 2018).

Every page below links to its Markdown version. Any page also returns Markdown when requested with `Accept: text/markdown`.

## Pages

- [Home](https://www.shreejitverma.com/index.md): Profile, experience, research, projects, skills, education, GitHub activity, and writing
- [Resume](https://www.shreejitverma.com/resume.md): Full resume as a web page, including certifications
- [Trishul case study](https://www.shreejitverma.com/work/trishul.md): AI-integrated FPGA market-making system (MS thesis): sub-10us tick-to-trade design and results
- [Writing](https://www.shreejitverma.com/writing.md): Technical articles on low-latency systems and market risk
- [FRTB for Engineers: What a Market Risk Capital Engine Actually Computes](https://www.shreejitverma.com/writing/frtb-for-engineers.md): 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.
- [Value Intelligence Platform](https://www.shreejitverma.com/value-investing.md): Reproducible value-investing screen with a deterministic multi-factor scoring engine
- [Reading List](https://www.shreejitverma.com/books.md): Curated finance and engineering library

## Machine-readable

- [Resume (JSON Resume)](https://www.shreejitverma.com/resume.json): the full resume in the jsonresume.org schema
- [Resume (PDF)](https://www.shreejitverma.com/Shreejit_Verma_Resume.pdf): downloadable resume
- [Search API](https://www.shreejitverma.com/api/search?q=market%20making): keyword search with source URLs; described by [OpenAPI](https://www.shreejitverma.com/openapi.json)
- [MCP server](https://www.shreejitverma.com/mcp): read-only streamable HTTP MCP server, no authentication ([Server Card](https://www.shreejitverma.com/mcp/server-card))
- [A2A agent](https://www.shreejitverma.com/a2a): JSON-RPC agent for profile questions ([Agent Card](https://www.shreejitverma.com/.well-known/agent-card.json))
- [Agent Skills](https://www.shreejitverma.com/.well-known/agent-skills/index.json): how an agent should use these endpoints
- [AI Catalog](https://www.shreejitverma.com/.well-known/ai-catalog.json) and [API Catalog](https://www.shreejitverma.com/.well-known/api-catalog): discovery manifests
- [Full content](https://www.shreejitverma.com/llms-full.txt): every page in one Markdown file

## Profiles

- [GitHub](https://github.com/shreejitverma)
- [LinkedIn](https://www.linkedin.com/in/shreejitverma/)
- [Google Scholar](https://scholar.google.com/citations?hl=en&user=qMzU8iAAAAAJ)

## Contact

- Email: shreejitverma@gmail.com
- Book a call: https://calendly.com/shreejitverma