Job Description
Are you a visionary engineer looking to disrupt the financial markets? OptionFlow Technologies is seeking a highly skilled Software Engineer specializing in quantitative finance to join our dynamic team in Portland, Oregon. We are building next-generation infrastructure for real-time equity options analytics, and we need a technical expert to help us scale our pricing engines and data pipelines.
In this role, you will bridge the gap between complex mathematical models and scalable software architecture. You will work closely with quantitative analysts to implement pricing models, optimize latency for high-frequency trading signals, and ensure our systems remain robust under market volatility.
Responsibilities
- Develop & Maintain Pricing Engines: Design, implement, and optimize core pricing algorithms for equity options using Python and C++.
- Market Data Integration: Integrate with high-speed market data feeds (e.g., CME, ICE) to ingest options chain data and update pricing models in real-time.
- Data Pipeline Architecture: Build scalable ETL pipelines to process large volumes of historical and streaming financial data.
- Backtesting Frameworks: Create robust testing environments to validate trading strategies against historical market scenarios.
- System Optimization: Identify bottlenecks in existing codebases and refactor for improved performance and scalability.
- Collaboration: Work alongside quants and traders to translate complex financial requirements into technical specifications.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative field.
- Programming Proficiency: Strong expertise in Python and C++, with a deep understanding of object-oriented design.
- Financial Knowledge: Solid understanding of financial derivatives, specifically equity options (Black-Scholes, Greeks, implied volatility).
- Database Skills: Experience with SQL (PostgreSQL) and NoSQL databases (MongoDB/Elasticsearch) for data storage and retrieval.
- Systems Knowledge: Familiarity with Unix/Linux environments, Docker, and cloud infrastructure (AWS/GCP).
- Problem Solving: Ability to solve complex, ambiguous problems with creative technical solutions.