Quantitative Portfolio Strategist, Information Technology
New York, New York, United States
Duties: Perform research using IT tools on option pricing data to improve data quality of borrow rates, dividend curves and volatility surfaces. Apply quantitative information technology techniques to extract alpha model strategies from large datasets. Perform quantitative analysis on intraday and multiday PnL attribution of equity option positions. Conduct research on improving option risk exposures such as gamma, vega, volga and vanna risks. Work on research projects on parametric volatility surface modeling and fitting. Lead research efforts to leverage innovative computer science techniques for options modeling tasks. Conduct research and building risk models using IT tools to identify option factors relevant to equity options risk across different strikes and expiries.
Minimum education required: PhD degree or equivalent in Computer Science, Computer Engineering, Mathematics, Statistics, Finance, Financial Engineering, Economics, or related field.
Minimum experience required: 0
Must also pass Company’s required skills assessment.
Must have demonstrated knowledge of cleaning, modifying and analyzing large-scale data sets.
Must have demonstrated knowledge of statistical modeling of large scale data, including advanced robust statistical and time-series models, and machine learning models.
Must have demonstrated knowledge of mathematical optimization including designing optimization utility functions and analyzing optimized parameters.
Must have demonstrated knowledge of Bash, Python and Java and data analysis packages including Python numpy, pandas, scipy, matplotlib, and scikit-learn.
Must have demonstrated knowledge of developing large and complex computer systems.
Must have demonstrated knowledge of US security markets, such as equity markets and option markets.
Must have demonstrated knowledge in financial data analysis, such as analyzing P&L, P&L attribution, corporate actions.
Must have demonstrated knowledge in Calculus, Probability theory, Linear Algebra, and Stochastic Calculus.