Quantitative Research [Multiple Positions Available]

Duties: Contribute to the strategic agenda to further transform equities trading into a data-led business and drive change through innovation and business process optimization using state-of-the-art electronic trading techniques. Work closely with trading to build analytics and data-driven processes that automate and optimize trading quantitatively, with special focus on ETF trading. Contribute from idea generation to production implementation. Perform research, design prototype, implement analytics and trading algorithms, support daily usage and analyze performance. Develop pricing models for market making activities taking into consideration alpha signals, quantitative features, and historic behavior using statistics, machine learning or heuristics. Work with the business to recycle risk and devise hedging strategies accordingly. Use of order book dynamics and electronic trading algorithms.

QUALIFICATIONS:

Minimum education and experience required: Bachelor's degree in Economics, Computer Engineering, Computer Science, Mathematics, Physics, Statistics, or related field of study plus 4 years of experience in the job offered or as Quantitative Research, or related occupation. The employer will alternatively accept a Master's degree in Economics, Computer Engineering, Computer Science, Mathematics, Physics, Statistics, or related field of study plus 2 years of experience in the job offered or as Quantitative Research, or related occupation.

Skills Required: This position requires experience with the following: Develop risk analytics using portfolio factor models including Barra and Axioma; building end to end automated and real time trading solutions using peer to peer messaging protocols Including AMPS, Tibco RV and Kafka; design and implementation of systematic hedging solution using Python; using statistical and machine learning packages including SciPy, XGBoost and Matplotlib to optimize trade execution; using Tableau and Matplotlib to view historical data simulation and build framework for automated decision making using machine learning and statistical libraries including stats, sci-kit learn, and TensorFlow; using time series databases including KDB to develop software systems; Conduct trading strategy research using Object Oriented Languages including Python, C++ and Java; utilizing decision driven analytics from data stored in KDB in Object Oriented Language.

Job Location: 270 Park Avenue, New York, NY 10017.

Full-Time. Salary:  $210,000 - $285,000 per year.