Job Description
We are seeking a highly analytical and detail-oriented Equity Options Data Analyst to join our growing team in Charlotte, North Carolina. This is an urgent hire opportunity for a professional who thrives in a fast-paced financial environment and has a passion for derivatives analytics.
In this role, you will be the critical link between raw market data and strategic trading decisions. You will manage large-scale datasets, validate pricing models, and deliver actionable insights that drive profitability. If you have a knack for uncovering trends in volatility and interest rates, we want to hear from you.
Key Highlights:
- Work with top-tier financial institutions in the Charlotte metro area.
- Utilize cutting-edge data science tools to optimize trading strategies.
- Competitive salary and comprehensive benefits package.
Responsibilities
- Analyze historical and real-time equity options data to identify trends in implied volatility and delta hedging.
- Build and maintain complex SQL queries and Python scripts to automate data extraction and reporting.
- Design interactive dashboards (Tableau/PowerBI) to visualize open interest, volume, and Greeks for senior management.
- Collaborate with quantitative researchers to validate the accuracy of Black-Scholes and Monte Carlo pricing models.
- Ensure data integrity and compliance with SEC regulations regarding derivatives disclosure.
- Produce weekly market commentary reports highlighting key risk factors and opportunities.
Qualifications
- Bachelor’s degree in Finance, Economics, Mathematics, Statistics, or Computer Science (Master’s preferred).
- 3+ years of professional experience in financial data analysis or quantitative research.
- Strong proficiency in SQL, Python (Pandas, NumPy), and Excel (VBA).
- Deep understanding of equity options, futures, and the mechanics of the derivatives market.
- Experience with data visualization tools and financial modeling software.
- Exceptional problem-solving skills and the ability to communicate complex data findings clearly.