Asset Management, QT Fund, Quantitative Alpha Researcher, ANL/ASO

We Offer
Cultural diversity is essential to our success. As such, we employ people from more than 100 countries. Credit Suisse empowers employees to work openly and respectfully with each other and with clients, ultimately striving to deliver superior results while offering initiatives and programs to assist employees achieve a healthy work-life balance.

QT Fund LTD:

The Fund's investment objective is to deliver a consistent, low volatility, positive return stream with limited drawdowns.

The Investment Manager seeks to achieve this objective by developing and running a variety of quantitative, systematic trading and investment strategies. Specifically, the Investment Manager's personnel formulate hypotheses about the drivers of asset returns and apply a rigorous scientific approach to design, develop, implement and manage strategies around these hypotheses.

We Offer:
  • A researcher role with the QT fund to research and develop alpha signals which will be reviewed by the fund Investment Committee and deployed into a central trading book.
  • Collect, clean, validate, and analyze large amounts of data in an effort to develop new sources of alpha for Systematic or Market Liquidity Strategies.
  • Utilize complex statistical and mathematical tools, probability theory, and optimization methods to balance risk/return tradeoff while incorporating risk control tools.

Credit Suisse maintains a Working Flexibility Policy, subject to the terms as set forth in the Credit Suisse United States Employment Handbook.

You Offer
  • 1-2 Years' Experience developing short term alpha signals for buyside or sellside.
  • Prior experience of developing quantitative strategies and managing the risks of the Portfolio.
  • 1-2 years Prior experience focused on execution optimization for short term trading strategies.
  • Strong work ethic, highly organized, detail-oriented, and motivated to drive projects.
  • Strong communication skills.
  • Strong quantitative skills, prefer candidate with an advanced degree from a leading academic institution.
  • Fluent in at least one statistical language, e.g. Matlab, R, SPlus.
  • Strong communication skills.

  • Capable to work and perform under pressure in a fast-paced environment.
  • Intellectual curiosity.