Job Description
Join Quantum Financial Analytics as an Entry-Level Equity Options Data Analyst and launch your career in finance! We're seeking analytical minds passionate about market data and derivative instruments. You'll work with our team to transform complex equity options data into actionable insights, supporting traders and portfolio managers. This is your gateway to Wall Street without the NYC commute – enjoy Milwaukee's vibrant tech scene while building expertise in quantitative finance.
Our collaborative environment offers mentorship from industry veterans and exposure to real-time market analytics platforms. You'll gain hands-on experience with options pricing models, volatility analysis, and risk metrics that drive multi-million dollar decisions. If you thrive on data puzzles and want to impact financial markets, this role is your perfect starting point.
Responsibilities
- Analyze equity options market data using SQL and Python to identify trading patterns and anomalies
- Build and maintain automated reports for options Greeks, implied volatility surfaces, and open interest trends
- Support validation of options pricing models through backtesting and sensitivity analysis
- Collaborate with traders to develop custom analytics dashboards in Power BI/Tableau
- Monitor market events and regulatory changes affecting equity options strategies
- Document data methodologies and ensure compliance with FINRA/SEC regulations
- Present findings to cross-functional teams using clear visualizations and narratives
Qualifications
- Bachelor's degree in Finance, Mathematics, Statistics, Computer Science, or related field
- 0-2 years of experience with financial data analysis, internships welcome
- Proficiency in SQL for data extraction and manipulation
- Strong knowledge of Excel (VLOOKUP, PivotTables, INDEX/MATCH)
- Familiarity with options basics (calls/puts, moneyness, expiration cycles)
- Basic Python skills (Pandas, NumPy) or willingness to learn
- Excellent problem-solving skills with attention to detail
- Ability to communicate complex concepts to non-technical stakeholders