Delta One Quant Researcher – Futures & Options

Drweng

Chicago (IL)

Vor Ort

USD 150.000 - 250.000

Vollzeit

Vor 5 Tagen
Sei unter den ersten Bewerbenden
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Benefits dieser Stelle

Medical insurance
Dental and vision insurance
401k with discretionary employer match
Short and long-term disability
Life and AD&D insurance
Flexible spending accounts

Zusammenfassung

DRW, a Chicago-based diversified trading firm, seeks a Senior Quantitative Researcher – Delta One to lead research for delta-one futures strategies and associated signals within the FICC options platform.

The role emphasizes collaboration with traders and developers to translate research into production, rigorous backtesting, and improved execution under realistic costs and constraints.

Qualifikationen

  • 2+ years of experience in quantitative research supporting systematic trading.
  • Proven track record of developing quantitative signals deployed in production.
  • Fluency in Python and experience with large-scale financial datasets.

Aufgaben

  • Research, develop, and validate delta-one futures strategies across global markets.
  • Build quantitative signal frameworks to support futures strategies and options portfolios.
  • Develop hedging methodologies to improve risk management in the FICC options business.
  • Research directional options overlays using quantitative futures signals with traders.
  • Model and analyze strategy and portfolio risks including volatility and liquidity.
  • Collaborate with traders, developers, and infrastructure teams to productionize research.

Kenntnisse

Python
Quant research
Backtesting
Alpha generation
Signal research
Execution modeling

Ausbildung

Advanced degree

Jobbeschreibung

DRW, a Chicago-based diversified trading firm, seeks a Senior Quantitative Researcher – Delta One to lead research for delta-one futures strategies and associated signals within the FICC options platform.

The role emphasizes collaboration with traders and developers to translate research into production, rigorous backtesting, and improved execution under realistic costs and constraints.

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