State Street
Jun 2025 — present · Boston, MA
AVP, Quant — eFX
Sep 2026 — present
Quant — eFX
Jun 2025 — Sep 2026
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Optimized FIX session handling, reducing disconnects by 80%+ and eliminating associated
resubscription overhead across currency pairs and tenors, while reducing operational risk
from trade timeout incidents.
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Created AI bot infrastructure on an MCP server and the State Street AI API, automating
operational processes like position checks and opening access to proprietary data for
non-technical users.
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Built a scalable framework for AI-powered applications on TickDB, enabling rapid iteration
and deployment of future intelligence tools.
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Optimized skew class calculations, reducing latency and improving accuracy in real-time
quoting.
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Led automated monitoring and reporting enhancements across trading systems, reducing manual
oversight and improving operational visibility.
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Conducted self-guided research on signal generation and optimization, identifying ways to
improve portfolio performance.
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Pitched a new business opportunity leveraging existing database infrastructure to senior
leadership.
State Street
Jul 2024 — Jun 2025 · Boston, MA
Professional Development Program
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eFX Market Making
- Implemented and evaluated a high-frequency autoregressive model.
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Implemented Symphony API integration enabling real-time data access and interaction
within the messaging platform.
- Designed analysis tools to automate pricing evaluation and improve reporting efficiency.
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eFX Benchmarks
- Improved tooling for benchmarking execution performance and market selection effectiveness.
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Developed a visualization framework to streamline signal generator testing and validation
against production standards.
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Built a backtesting tool to analyze parameter changes and quantify PnL outcomes, enabling
data-driven optimization of execution strategy.
State Street
Jun 2023 — Aug 2023 · Cambridge, MA
Intern
- Used MATLAB to research and backtest an EM FX hedging strategy based on a deployed G10 approach.
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Worked with the Indirect and StreetFX sales teams to automate a daily task in Python, saving
5 hours a month.
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Combined proprietary indicator data with industry-standard signals to produce the August FX
Hedging Monitor publication.