Our Client is a statistical arbitrage hedgefund located in New York City. The role will involve working within a team environment on the design and development of systematic strategies for trading in equities. Projects vary but you are likely to focus on designing, testing and optimizing mid frequency stat-arb strategies. Working on computationally-intensive tasks such as dynamic modeling of mean-reverting spreads. Developing real-time estimation signals, constructing mean-reverting spreads, extracting predictive signals from noisy time series datasets, building algorithms for real-time estimation of the unobserved spread process in order to reveal temporary market inefficiencies which can then be exploited to generate excess returns, building time dependency into model parameters, testing alphas, construction, optimization of portfolios, building predictive functions such as linear estimators, optimizing based on specific constraints, running simulations and computational experiments to test strategies on data and prove a concept using out of sample data, fine tuning and parameter optimization,, building execution strategies leveraging DMA and Dark pools, building custom models to improve execution efficiencies.
Skills and Qualifications
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