Jobs · Research · New York

HFT Quantitative Research and Trading

DeepFin Research · New York, NY · 2 wk ago
HybridResearchFull-time

The Role

We are looking for exceptional HFT Quantitative Researchers and Traders to work at the intersection of research, engineering, low-latency execution, creating alpha and monetising our deep-learning alpha across a broad spectrum of markets, products, and asset classes.

Key Responsibilities

  • Monetise core alpha through efficient execution strategies across futures and related products.
  • Expand trading universes - identify and onboard new instruments within existing markets and work closely with BD to identify new opportunities and exchanges.
  • Develop and refine execution logic - optimise market access, routing, and order placement to minimise slippage and latency impact.
  • Collaborate closely with researchers, developers, and infrastructure engineers to bring models from research to production.
  • Design and test short-term signals and execution algorithms to preserve alpha and reduce transaction costs.
  • Maintain and monitor live strategies, diagnose performance drift, and implement continual improvements.
  • Conduct PnL attribution and microstructure analysis to measure and enhance monetisation efficiency.
  • Stay ahead of exchange microstructure changes and proactively adapt strategies to evolving market dynamics and market impact dynamics.

Ideal Candidate Profile

  • 5+ years of experience in HFT or ultra-low-latency trading, ideally within futures markets (options experience is a strong plus).
  • Proven track record in execution alpha monetisation - not just signal generation - you’ve taken models from idea to production.
  • Deep understanding of L3 data, market microstructure, order book dynamics, and short-horizon predictive models.
  • Hands-on experience in strategy deployment and productionisation, including calibration, risk controls, and post-trade analytics.
  • Strong quantitative and programming skills - Python and C++ preferred; familiarity with distributed and low-latency systems advantageous.
  • Knowledge of cross-exchange arbitrage, market making, or execution cost optimisation a plus.
  • Highly analytical, commercial mindset with the ability to operate autonomously in a fast-paced, research-driven environment

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