Senior HFT Quant Trader: Deep-Learning Alpha

DeepFin Holdings Ltd; New York (NY); On-site; USD 250,000 - 400,000; Full time

Job summary

DeepFin Holdings Ltd is seeking exceptional HFT Quantitative Researchers and Traders to join our team at the intersection of research, engineering, and low-latency execution. You will help monetise alpha across futures and related products while expanding the universe of tradable instruments.

You will collaborate with researchers, developers, and infrastructure engineers to bring models from research to production, design fast-execution logic, and monitor live performance to continually improve

Qualifications

• 5+ years of experience in HFT or ultra-low-latency trading.
• Proven track record in monetising alpha through execution.
• Deep understanding of market microstructure and order-book dynamics.

Responsibilities

• Monetise core alpha through efficient execution strategies across futures and related products.
• Expand trading universes by onboarding new instruments with BD involvement.
• Develop and refine execution logic to minimise slippage and latency impact.
• Collaborate with researchers, developers, and infra engineers to productionise models.
• Design and test short-term signals and execution algorithms to preserve alpha and reduce costs.
• Monitor live strategies, diagnose performance drift, and implement continual improvements.
• Conduct PnL attribution and microstructure analysis to measure monetisation efficiency.
• Stay ahead of exchange microstructure changes and adapt strategies accordingly.

Skills

HFT experience

Low-latency trading

Quantitative research

Python

C++

Tools

Distributed systems

Low-latency infrastructure

Job description

DeepFin Holdings Ltd is seeking exceptional HFT Quantitative Researchers and Traders to join our team at the intersection of research, engineering, and low-latency execution. You will help monetise alpha across futures and related products while expanding the universe of tradable instruments.

You will collaborate with researchers, developers, and infrastructure engineers to bring models from research to production, design fast-execution logic, and monitor live performance to continually improve