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OpenQuant
2023-02-16

Trader

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DRW
Trader
Chicago, US
150,000 - 170,000
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Job Description

 Responsibilities:

  • Execute trades using various systems within DRW on behalf of multiple risk-taking desks.

  • Develop an expertise in execution tools and market microstructure to manage orders, trades, and positions.

  • Research and identify fundamental drivers of asset prices across financial, macroeconomic, and alternative datasets to generate new trade ideas.

  • Work across a wide array of products that may include: Equities, Commodities, Rates, FX markets in the cash, futures and options instruments.

  • Build quantitative tools and models to extract key insights from market data and directly guide risk taking decisions.

  • Write code in Python or other scripting languages to develop alerts and tools that inform discretionary trading strategies.

  • Initiate actionable business recommendations to onboard new products, optimize execution strategies, and improve trading software using data and insights gathered from first-hand trading experience.

  • Form, communicate and present data-driven recommendations to leadership in collaboration with team members.

  • Assist in the execution of new business initiatives, driving projects to completion.

Requirements:

  • Bachelor’s degree in Computer Science, Engineering, Math, Statistics, or related field and two years of experience executing trades and managing risk.
  • Industry experience to include: (1) Execute and monitor trades in futures and at least two of the following asset classes (stocks, options, and/or foreign exchange) on various trading platforms such as Bloomberg, TT, or in-house software; (2) Python programming skills to explore large financial datasets using data analysis libraries such as Pandas, Numpy, Matplotlib, Scikit-Learn, etc.; (3) Executing trades for multiple portfolio managers with diverse trading styles in a fast-paced, high pressure environment; (4) Background in analyzing order book and tick data to study market microstructure; and (5) Exposure to applying machine learning, linear programming, numerical analysis, or statistical methods to identify patterns in trading data.
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