Job Description
We are seeking a highly analytical Equity Options Data Analyst to join our dynamic team in Indianapolis. In this pivotal role, you will bridge the gap between complex market data and actionable trading strategies. We pride ourselves on our modern, high-performance culture and offer a competitive benefits package including Daily Pay options for our valued employees.
As a key member of our quantitative research division, you will be responsible for maintaining our high-fidelity data pipelines and providing deep insights into options flow and market sentiment. If you are passionate about financial markets and possess a sharp eye for data integrity, we want to hear from you.
Why Join Us?
- Remote-First Culture: Work from the comfort of your home in Indianapolis or anywhere in the US.
- Daily Pay Option: Access your earnings daily with our flexible pay structure.
- Modern Tech Stack: Work with the latest tools in Python, SQL, and cloud infrastructure.
Key Responsibilities
Responsibilities
- Extract, clean, and validate large datasets from multiple exchanges and dark pools for equity options trading.
- Develop and maintain interactive dashboards (using Tableau, PowerBI, or Looker) to visualize options flow, open interest, and implied volatility.
- Collaborate with the trading desk to identify data anomalies and provide actionable insights for risk management.
- Perform backtesting of options pricing models and strategies using historical data.
- Ensure data latency is minimized to support high-frequency decision-making processes.
- Automate data ingestion workflows using Python scripts and SQL queries.
Qualifications
- Bachelor’s degree in Finance, Mathematics, Statistics, Computer Science, or a related quantitative field.
- 3+ years of experience in data analysis, preferably within the financial services or equity derivatives sector.
- Proficiency in SQL (PostgreSQL, MySQL) and Python (Pandas, NumPy, Scikit-learn).
- Strong understanding of options pricing theory (Black-Scholes, Greeks) and market microstructure.
- Experience with data visualization tools (Tableau, Looker, or D3.js).
- Excellent communication skills, capable of translating complex data into clear business recommendations.