Job Description
Join the forefront of financial intelligence with our urgent hiring campaign for an Equity Options Data Analyst in Detroit, MI.
We are seeking a highly analytical and detail-oriented professional to join our elite data science team. In this role, you will be responsible for transforming complex equity options data into actionable insights that drive our trading strategies and risk management protocols. If you thrive in a fast-paced, high-impact environment and possess a deep understanding of financial derivatives, we want to hear from you.
Why Apply?
- Competitive Compensation: $95,000 - $145,000 base salary plus performance bonuses.
- Urgent Start: Immediate opening for the right candidate.
- Modern Tech Stack: Work with Python, SQL, and cloud-based data warehousing.
Don't miss this opportunity to advance your career in the heart of Michigan's financial sector.
Responsibilities
- Advanced Data Processing: Design and implement ETL pipelines to ingest, clean, and validate massive datasets from equity options exchanges in real-time.
- Market Analysis: Perform quantitative analysis on options pricing, volatility surfaces, and open interest to identify market trends and arbitrage opportunities.
- Dashboard Development: Build interactive, high-performance data visualization dashboards (using Tableau or PowerBI) to communicate complex data findings to senior stakeholders and the trading floor.
- Model Validation: Assist in the validation and stress-testing of options pricing models (e.g., Black-Scholes, Monte Carlo simulations).
- Reporting: Generate comprehensive weekly and monthly performance reports highlighting key metrics and risk exposures.
Qualifications
- Education: Bachelor’s or Master’s degree in Finance, Mathematics, Statistics, Computer Science, or a related quantitative field.
- Experience: Minimum of 3-5 years of experience in data analysis, specifically within the financial derivatives or equity options sector.
- Technical Skills: Proficiency in SQL (Advanced), Python (Pandas, NumPy), and experience with big data technologies (Spark, Hadoop) is highly preferred.
- Financial Knowledge: Strong understanding of equity options mechanics, Greeks (Delta, Gamma, Vega, Theta), and market microstructure.
- Problem Solving: Ability to troubleshoot complex data anomalies and derive logical conclusions from unstructured data sets.