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Part-Time Opportunity: AI-Powered Quantitative Trading Project (Culver City)

Negotiable Salary

4166 Jasmine Ave, Culver City, CA 90232, USA

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Part-Time Opportunity: AI-Powered Quantitative Trading Project (Equities Market) Are you a Computer Science major with a passion for the stock market and a solid foundation in quantitative analysis? We are looking for a technically driven and analytically minded individual to join a part-time project focused on building and optimizing an AI-powered automatic trading system for the equities market. About the Role You will work on the design and implementation of algorithmic trading strategies, integrating statistical modeling and machine learning to identify trading opportunities and execute automated trades. The project will involve: Developing, testing, and refining automated trading algorithms Leveraging machine learning models to improve predictive accuracy Applying quantitative/statistical analysis to evaluate financial data Working with real-time market data, APIs, and execution platforms Ideal Candidate Current Computer Science major (or recent grad) with strong programming skills Solid understanding of equities, financial markets, and trading principles Experience or coursework in quantitative analysis, data science, or statistics Proficient in Python (preferred), with experience using libraries like pandas, NumPy, scikit-learn, or PyTorch Bonus: Familiarity with trading APIs (e.g., Alpaca, Interactive Brokers, Robinhood, etc.) Why Join? Gain real-world experience applying CS and AI to live market trading Work on a cutting-edge fintech project with real market exposure Flexible, remote, part-time engagement with opportunities to grow If you're excited about building intelligent trading systems and applying your CS and analytical skills in a dynamic financial setting, we want to hear from you. Apply by sending your resume and a brief statement of interest to halston@savoyactive.com.

Source:  craigslist View Original Post

Location
4166 Jasmine Ave, Culver City, CA 90232, USA
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