Overnight Algorithmic Trading Quant Jobs (NOW HIRING)

A proprietary trading firm based in Miami is seeking a highly motivated Quantitative Trading Intern to join the team as an intern. In this role, you will apply analytical thinking and market intuition to pricing, execution, and risk decisions as part of the firm's quantitative trading team.

This is an ideal opportunity for students and recent graduates who are passionate about financial markets, probability, game theory, technology, and fast-paced decision-making. The work spans quant trading, algorithmic trading, market making, probability, execution, and risk management. You will work closely with experienced traders, quantitative researchers, and engineers to learn how modern strategies, models, and trading systems are designed, tested, and implemented.

The team is small, technical, and collaborative, with direct access to experienced traders, quantitative researchers, engineers, high-quality market data, and modern research infrastructure.

This is an on-site opportunity based in Miami, United States.

Requirements

- Analyze trading scenarios, pricing behavior, and risk tradeoffs.

- Build small research tools for market and strategy review.

- Practice clear reasoning under uncertainty.

- Monitor and analyze real-time market data to identify trading opportunities.

- Support the development, testing, and refinement of quantitative trading strategies.

- Make fast, data-informed trading decisions while managing risk.

- Conduct statistical analysis on historical and live market data.

- Evaluate market microstructure, liquidity, volatility, and other drivers of price movement.

- Participate in trading simulations, training programs, and strategy review sessions.

- Communicate trade ideas, risks, and performance insights clearly to the team.

- Continuously improve decision-making through feedback, research, and post-trade analysis.

- Current student from any degree discipline with strong numerical and analytical reasoning.

- Comfort with probability, mental math, coding, or strategy games.

- Interest in learning trading and market making; no prior quant or finance experience is required.

- Currently enrolled in any degree discipline and interested in building practical analytical skills.

- Evidence of curiosity and problem-solving through coursework, employment, projects, competitions, hobbies, or self-study.

- Strong quantitative, analytical, and problem-solving skills.

- Interest in financial markets, trading, probability, strategy games, or competitive problem-solving.

- Ability to make decisions quickly and remain calm under pressure.

- Strong attention to detail, intellectual curiosity, and a disciplined approach to risk.

- Programming experience in Python or a similar language is preferred.

- Prior internship, research, trading competition, or personal project experience is a plus but not required.

- Applicants from every degree discipline are welcome.

- No prior quantitative finance, trading, or investment-industry experience is required.

- Strong attention to detail, intellectual curiosity, and a commitment to continuous improvement.

- Excellent communication and teamwork skills.

The ideal candidate is intellectually curious, competitive, numerically strong, and comfortable making decisions with incomplete information. You enjoy solving complex problems, thinking strategically, learning from feedback, and working in a fast-moving environment where performance and precision matter.

Benefits

- Comprehensive training in trading, market structure, risk management, and quantitative strategy development.

- Mentorship from experienced quantitative traders, researchers, engineers, and technologists.

- Exposure to live markets, real financial datasets, and the full path from idea to implementation.

- A collaborative, high-performance environment that values curiosity, discipline, and continuous learning.

- Opportunities for rapid growth based on performance, ownership, and measurable impact.

- Competitive compensation and a benefits package aligned with the employer and location.