Quant Trader - ML​/AI; NYC

We are hiring Machine Learning–Driven Quantitative Traders at Quantitative Strategies Group (QSG)

👉 Apply only through our website:

Applications submitted via Linked In messages or recruiters will not be reviewed.

Quantitative Strategies Group (QSG) is a proprietary trading firm that trades firm capital only. Traders build long-term trading businesses inside the firm with real ownership, real accountability, and real risk.

This is not a salaried role, not a training program, and not a research‑only position. Capital allocation, responsibility, and compensation are earned over time based entirely on performance, discipline, and risk management.

This is a New York City role. Office trading floor access is available and NYC‑based candidates are strongly preferred.

Traders manage their own account within the firm and build systematic strategies using firm capital while leveraging QSG’s infrastructure and risk framework. From day one, traders contribute directly to research, strategy development, and implementation. Risk limits scale over time based on demonstrated performance, discipline, and adherence to risk constraints.

Traders operate independently while benefiting from shared firm infrastructure including capital, technology, market access, risk management, and ongoing internal education.

We are looking for people with real machine learning depth and strong quantitative instincts.

Not just the ability to use models, but the ability to build and understand them. If you like finding opportunities, forming hypotheses, testing them empirically, and fixing real problems, you will fit well here.

This can be a strong fit for academically trained candidates who do not want a traditional research path and prefer working on real systems, real data, and real feedback loops.

• Authorized to work in the United States without employer sponsorship now or in the future
• Demonstrated experience building machine learning models in a serious, hands‑on way
• Ability to clearly explain what you built, why it worked, and what broke

• Understand assumptions, architecture, and tradeoffs behind what they build
• Have strong instincts around overfitting, leakage, robustness, and out‑of‑sample testing
• Enjoy being a finder and problem solver, not just an “ML user”
• Operate with an entrepreneurial mindset: self‑directed, accountable, motivated by long‑term ownership
• Value continuous learning and fast iteration

Prior live trading experience is not required, but candidates must demonstrate serious quantitative work and the ability to execute ideas independently.

• Compensation:
  Fully performance‑based profit share based on net trading profits. No base salary and no guaranteed compensation. (NYC pay transparency: $0–$0 base pay/rate.)
• We prioritize candidates who defer intuition to data and are willing to discard ideas that fail empirical validation
• Applications that do not demonstrate hands‑on quantitative or technical work will not be competitive
• We do not review applications submitted via Linked In messages or recruiters