Associate with Goldman Sachs & Co. LLC in New York, NY.
Work Schedule: 40 hours per week (9:00 a.m. to 6:00 p.m.)
Duties: Associate with Goldman Sachs & Co. LLC in New York, NY. Work within the Goldman Sachs Execution Solutions business unit to perform statistical analysis of algorithmic execution strategies by analyzing market structure and execution data. Customize algorithmic trading strategies based on the results of historical analysis to improve execution performance. Improve existing and develop novel execution strategies using optimization and related numerical techniques. Present findings to quantitative asset managers. Develop new analytics and metrics to analyze performance of electronic trading strategies. Must be willing to work with proprietary technology. No proprietary knowledge is required pre-hire.
Job Requirements: Master’s degree (US or foreign equivalent) in Mathematics, Statistics, Computer Science or related analytical field. Two (2) years of experience in the job offered or related position. Prior work experience must include two (2) years with: applying optimization and numerical techniques to derive and implement solutions using mathematical software, including Python, R or C++; utilizing knowledge of financial mathematics, including stochastic calculus, linear algebra, probability and/or random processes; performing statistical analysis of large and high dimensional real time market data datasets; demonstrating direct client-facing front desk experience to explain and improve algorithmic trading strategies; applying knowledge of equity markets and market microstructure to customize trading algorithms, as well as conducting analysis of large trades and complex strategies; and time series analysis and manipulation of large datasets. Prior work experience must include six (6) months with utilizing programming skills to interpret functionality of algorithmic equity trading strategies in object oriented programming languages such as Java or C++. Travel required domestically to visit clients (approx. twice/quarter).
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