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New Grad Full-Time Quantitative Trader

WallStreetQuants

Job Description

Job Description

About the Role

Proprietary trading firm based in New York City is seeking a highly motivated New Graduate Quantitative Trader to join the team full-time. 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 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 a hybrid opportunity based in New York, United States.

Requirements

Responsibilities

- Reason through pricing, risk, and execution decisions.

- Analyze trade outcomes and market behavior with data.

- Build disciplined habits around probability, sizing, and feedback loops.

- 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.

Qualifications

- Final-year student or recent graduate from any degree discipline with strong analytical instincts.

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

- Interest in learning within a fast-feedback trading environment; no prior quant or finance experience is required.

- Final-year student or recent graduate from any degree discipline who is ready to begin a full-time role.

- No specific academic major is required; analytical ability and learning speed matter more than subject studied.

- 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.

Ideal Candidate

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

What We Offer
  • 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.
  • Competitive compensation and benefits package.

Vacancy posted 6 days ago
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