Financial analysts need reliable pricing and risk tooling across swaps, bonds, curves, FX forwards, FX swaps, FX options, and equity options without scattering logic across spreadsheets and one-off scripts.

Quant Copilot centralises financial mathematics in a tested Python quant-core library, exposes it through a FastAPI backend, and provides analyst-facing Streamlit workflows.

• Quant analysts
• Treasury teams
• Risk teams
• Fixed-income desks
• Analyst workbench users

Internal desk tooling, institutional analytics licensing, model validation workbench, and enterprise deployment for pricing and risk workflows.

Layered product architecture with quant-core for financial mathematics, FastAPI for HTTP orchestration, and Streamlit for the analyst workbench.

• Python
• FastAPI
• Streamlit
• Pydantic
• Pytest

Product architect and builder responsible for quantitative product design, separation of concerns, backend/API workflow, and analyst UI direction.

• quant-core test suite passes: 678 tests.
• FastAPI backend test suite passes: 902 tests.
• Streamlit smoke and live integration suite passes: 9 tests after adding the missing pytest dependency.
• Covers IRS pricing, FRA pricing, FX forwards, FX swaps, FX options, equity options, mixed curve building, risk ladders, scenarios, bond pricing, bond risk, and YTM solving.

• Maintain clean dependency audits across Python product surfaces.
• Harden deployment packaging for backend and Streamlit surfaces.
• Add user documentation, model governance notes, and production deployment runbooks.
• Expand future modules for Greeks, Monte Carlo, and advanced options workflows.