HFT Quant

Annonymous; New York (NY); On-site; USD 180,000 - 320,000; Full time

Job summary

Non pod multi-strategy hedge fund in New York is seeking an exceptional mid to sr Quant Researcher to develop and expand algorithmic trading strategies across U.S. equities.

The role emphasizes intraday alpha generation through market microstructure, order flow, and short-horizon prediction. You will own the research process from hypothesis to backtesting and live deployment, partnering with traders and researchers to rigorously test signals and productionize robust strategies.

Qualifications

• Proven experience developing intraday algorithmic trading strategies.
• Strong understanding of market microstructure, limit-order books, execution dynamics and high-frequency data.
• Exceptional statistical and quantitative modeling skills.
• Track record of taking research ideas from hypothesis through backtesting and live deployment.

Responsibilities

• Develop novel intraday trading signals using tick-level market data, order-book information, and other datasets.
• Research market microstructure, liquidity, order flow, price formation, and short-term return dynamics.
• Design, backtest, and optimize algorithmic trading strategies with emphasis on robustness and scalability.
• Develop predictive models and identify new sources of short-horizon alpha.
• Analyze live strategy performance, attribution, and execution quality, refining signals and models.

Skills

Intraday trading

Algorithmic trading

Market microstructure

Statistical modeling

Backtesting

Job description

Non pod multi-strategy hedge fund in New York is seeking an exceptional mid to sr Quant Researcher to develop and expand algorithmic trading strategies across U.S. equities.

The role is focused on intraday alpha generation, with an emphasis on market microstructure, order flow, short-horizon prediction, and exploiting transient market inefficiencies. The successful candidate will have significant ownership of the research process, signals development, rigorous testing and production implementation.

Responsibilities

• Develop novel intraday trading signals using tick-level market data, order-book information, and other proprietary or alternative datasets.
• Research market microstructure, liquidity, order flow, price formation, and short-term return dynamics.
• Design, backtest, and optimize algorithmic trading strategies, with emphasis on statistical robustness and scalability.
• Develop predictive models and identify new sources of short-horizon alpha.
• Analyze live strategy performance, attribution, and execution quality, continuously refining signals and models.

Qualifications

• Proven experience developing intraday algorithmic trading strategies.
• Strong understanding of market microstructure, limit-order books, execution dynamics, and high-frequency financial data.
• Exceptional statistical and quantitative modeling skills.
• Track record of taking research ideas from initial hypothesis through backtesting and, ideally, live deployment.
• Candidates from leading HFT, algorithmic trading, quantitative trading, or electronic trading firms are particularly encouraged to apply.

This is a high-impact research role with significant autonomy, close interaction with experienced traders and researchers, and the opportunity to directly influence a growing algorithmic trading portfolio.