Central Risk Quant - Assoc/VP level Central Risk Quant - Assoc/VP level …

Anson McCade
in Manhattan, NY, United States
Permanent, Full time
Last application, 09 Jul 20
Negotiable
Anson McCade
in Manhattan, NY, United States
Permanent, Full time
Last application, 09 Jul 20
Negotiable
Anson McCade
Central Risk Quant - Assoc/VP level NY based

You will be part of the Equities Quant team and work closely with equity traders to develop tools, models, alpha signals and risk measures. You will contribute significantly to the development and enhancement of the algorithmic portfolio management system used to balance the risk, transaction costs, and expected return of the trading book. You will also be very closely involved with the trading desk and enhance their businesses via the strategic development of the modeling, risk, and trading infrastructure.


You will have prior experience building trading and risk management platforms, alpha signals, pre-, intra-, and post-trade analytics tools, and will also possess familiarity with execution algorithms. A working knowledge of market microstructure and algorithmic trading strategies is a plus. On a day-to-day basis, the role involves analyzing historical data, building mathematical models, and running back-tests and simulations using available internal and external trade, quote, and execution data sets. A substantial amount of coding is necessary on a daily basis in order to programmatically analyze, test, and implement models. You will work with a team consisting of traders, quantitative analysts, and technologists. A degree in science, engineering or mathematics is required, a master's or PhD is a plus.

Qualifications

  • Strong background in mathematical finance and statistical analysis is required.
  • PhD/ Masters in Maths / Physics / Statistics or related subjects.
  • At least two years of experience in the quantitative aspects of algorithmic trading is required with preference given to those with direct experience in Equities and the automated management of portfolio risk.
  • Strong technical programming (C++, Python, R, Q/KDB).
  • Knowledge of risk models and statistical analysis and portfolio management.
  • Track record in delivering production projects.
  • Show keen interest in the financial markets.
  • Strong team work capability.
  • Consistently demonstrates clear and concise written and verbal communication skills.
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