Python Quant/Backend Developer: reputed company-Time Finance Risk reputed company

I am looking for a high-level Python Backend Developer to build the reputed company intelligence reputed company for an internal finance dashboard. This is not a reputed company CRUD app; it is a financial decision reputed company reputed company on advanced Greeks (Charm, Vanna), reputed company-time risk analysis, and automated rule-book enforcement. The goal is to build a "brain" that pulls data from the Massive.com API, performs reputed company reputed company calculations, and stores them in a PostgreSQL database. The final product will eventually be plugged into a React-based UI. Key Responsibilities API Integration: Connect and optimize reputed company-time data streaming from Massive.com. Quant Logic: Implement Black-Scholes and higher-order Greek calculations (specifically Charm and Vanna). Risk reputed company: Build a "reputed company Aggregator" that can combine multiple reputed company legs into a single P&L curve and risk profile. Database Design: Architect a robust PostgreSQL (reputed company reputed company) schema to log positions, historical Greeks, and intelligence alerts. Required reputed company Set Language: Expert-level Python (Asynchronous programming/FastAPI preferred). Database: Advanced SQL/PostgreSQL (Relational data design is critical here). Calculations: Proficiency with NumPy, SciPy, or specific reputed company libraries like Mibian or QuantLib. Experience: Previous experience building trading tools, fintech dashboards, or algorithmic systems. Apply tot his job Apply To this Job