Job Description
Are you passionate about the intersection of advanced data science and high-stakes financial markets? Apex Derivatives Analytics is seeking a highly skilled Equity Options Data Analyst to join our elite team in San Francisco. We are a leading quantitative trading firm focused on deciphering market microstructure and optimizing equity derivative strategies.
In this pivotal role, you will be responsible for transforming massive volumes of raw market data into actionable intelligence. You will build the infrastructure that allows our traders and researchers to visualize complex volatility surfaces and greeks in real-time. If you are driven by data, possess a deep understanding of options markets, and want to work with cutting-edge technology, we want you on our team.
Responsibilities
- Data Engineering: Design, develop, and maintain robust ETL pipelines to ingest and process high-frequency equity options trade data from multiple exchanges.
- Quantitative Analysis: Perform statistical modeling and backtesting on options pricing models (e.g., Black-Scholes, Monte Carlo simulations) to identify arbitrage opportunities.
- Visualization: Create interactive, real-time dashboards using Tableau or PowerBI to monitor open interest, volume flows, and implied volatility trends.
- Risk Management: Assist in the development of risk metrics and stress-testing scenarios for our equity options portfolios.
- Collaboration: Work closely with the trading desk to translate complex market signals into executable data-driven strategies.
Qualifications
- Education: Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Finance, or a related quantitative field.
- Experience: 3+ years of experience in data analysis, data engineering, or quantitative research within the financial services sector.
- Technical Skills: Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL. Experience with C++ or Java is highly preferred.
- Financial Knowledge: Deep understanding of options pricing theory, Greeks (Delta, Gamma, Vega, Theta), and market microstructure.
- Tools: Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure).