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Quantitative Trader - Digital Assets

Quantitative Trader - Digital Assets

Geneva TradingChicago, IL, US
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Quantitative Trader - Digital Assets

Founded in 1999, Geneva Trading is a premier global principal trading firm with strategically located offices in Chicago, Dublin, and London. Our relentless focus on trading excellence combined with technological innovation has equipped us with a best-in-class proprietary trading platform, enabling us to compete at the highest levels in the global markets. Rooted in a culture of integrity, collaboration, and an unwavering passion for progress, we foster an environment of personal and professional excellence. Our nimble organizational structure and entrepreneurial spirit attract top-tier talent with a passion for innovation, laying the foundation and driving our consistent success in the industry.

Geneva Trading is looking for ambitious, entrepreneurial students to join our quantitative trading internship program next summer for our digital assets team. Our internship program is a fast-paced, dynamic 10-week full-time paid position that gives you hands-on experience in the trading industry. Our interns are expected to design solutions to complex problems and work on projects that directly impact the firm. You'll receive mentorship by industry pros and will participate in corporate training, team building activities, and firm wide summer socials to strengthen your connection with other interns and full-time employees. The summer internship program is a path to earn full-time opportunities at Geneva Trading after graduation.

As a Quant Trading (Intern) You Will :

  • Undergo intensive kdb / q classroom and training
  • Model, analyze, and optimize existing and new trading opportunities
  • Develop and enhance tools to understand key drivers and indicators of profitability and risk
  • Answer questions for traders by quantifying the quantifiable and using inferences when data is imperfect

Required Qualifications :

  • Master's degree in financial engineering, Financial Mathematics, Computational Finance, or another STEM-related field of study
  • Graduation dates between December 2025 and June 2026
  • Understanding of statistical methods and experience employing optimization libraries and statistical packages (e.g. R or MATLAB)
  • Strong programming experience in Python
  • Overwhelming desire to solve problems and learn about market microstructure, financial markets, and algorithmic trading
  • Exposure to forecasting and data mining techniques, such as linear and non-linear regression analysis, neural networks, or support vector machines
  • Preferred Qualifications :

  • Prior experience with relationship databases
  • Prior experience with trading competitions, competitive gaming, poker, etc.
  • We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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