QUANTITATIVE RESEARCHER

Job Description

Duties : Utilize advanced mathematical, statistical and computational/computer science skills to research and build state‐of‐the‐art quantitative investment strategies. Research and apply mathematical and statistical principles, quantitative data analysis techniques, computer engineering principles, and market knowledge to large, often novel quantitative datasets to perform financial predictive analysis. Research, design, develop and back-test predictive quantitative financial models, by using advanced statistical learning, machine learning and data analysis skills in the application of mathematics and computer engineering principles. Apply numerical algorithms, statistical analysis, optimization techniques, and machine learning techniques including complex linear algebra, regression methods, time series methods, Bayesian Statistics, Kernel Machine techniques, Deep Neural Network, and stochastic optimizations to formulate and design sophisticated financial modeling systems. Develop production-quality, highly sophisticated, high reliability, high-tuned numerical program codes using complex linear algebra, statistical modeling and numerical optimization techniques to aid in the development of financial predictive model computer programs capable of processing, sorting, and comparing vast amounts of data which will drive investment decisions.

Minimum education required : Master’s Degree in Mathematics, Statistics, Computer Science, Operations Research, Physics or Computational Chemistry.

Minimum experience required : 0

Skills required: Must have knowledge of the following skills:

• Analyzing and modeling large, high-dimensional real world datasets;
• Advanced statistics including linear statistical models, probability theory, pattern recognition, regression methods, time series methods and Bayesian Statistics, and their applications in real world data analysis;
• Knowledge of numerical optimization methods and stochastic optimization algorithms, and their application in machine learning techniques;
• Advanced machine learning algorithms including Kernel Machine algorithms and Deep Neural Networks, and knowledge of using these sophisticated models in real world datasets;
• Research work conducting academic research in a highly quantitative field of science as evidenced by publication of research work in an academic peer-reviewed journal;
• Quantitative development in Java or C++, scripting languages (Python), as well as knowledge of numerical packages including Pandas/NumPy;
• The Linux/Unix environment and bash/shell scripting.

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