DeepFin Research

Deploys ML-driven systematic models across markets

HFT Quantitative Research and Trading

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours

Full-timeNo salary listedIn-person

About the Job

Requirements

At least 5 years of experience in high-frequency trading or ultra-low-latency trading, ideally in futures markets; options experience is a strong plus.
A proven track record in execution alpha monetization, including taking models from idea to production.
Deep understanding of Level 3 data, market microstructure, order book dynamics, and short-horizon predictive models.
Hands-on experience deploying and productionizing strategies, including calibration, risk controls, and post-trade analytics.
Strong quantitative and programming skills; Python and C++ are preferred.
Ability to work with distributed and low-latency systems is advantageous.
Ability to operate autonomously in a fast-paced, research-driven environment.

Responsibilities

Monetize core alpha through efficient execution strategies across futures and related products.
Expand trading universes by identifying and onboarding new instruments within existing markets and working with business development to identify new opportunities and exchanges.
Develop and refine execution logic by optimizing market access, routing, and order placement to minimize slippage and latency impact.
Collaborate 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.
Monitor live strategies, diagnose performance drift, and implement continual improvements.
Conduct profit-and-loss attribution and microstructure analysis to measure and enhance monetization efficiency.
Track exchange microstructure changes and adapt strategies to evolving market dynamics and market impact.

Desired Qualifications

Options experience.
Knowledge of cross-exchange arbitrage, market making, or execution cost optimization.

DeepFin is a systematic proprietary trading firm combining deep learning, traditional quantitative research methods, and cutting-edge trading technology, to trade global markets. Founded by engineers and researchers, we build and deploy advanced trading systems that operate across global markets.

Our team is lean, highly technical, and impact-driven - every hire plays a direct role in shaping the firm’s technology, strategy, and performance. We value curiosity, precision, and collaboration, and we’re building an environment where exceptional people can do their best work at the intersection of AI and financial markets.

HFT Quantitative Research and Trading

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 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.
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

If you’re passionate about applying advanced technology to real-world markets and want to work alongside a focused, high-performing team, we’d love to hear from you. DeepFin offers a collaborative, research-driven environment where ideas move quickly from concept to execution and where every contribution has visible impact.

Join us in building the next generation of deep-learning-driven trading systems - shaping the future of finance through innovation, rigour, and technology.

About the Company

DeepFin Research

Deploys ML-driven systematic models across markets

DeepFin Research builds quantitative investing tools by using machine-learning driven systematic models and applies them across global financial markets. Its approach centers on data-driven models that analyze market information to generate trading signals and guide decisions, aiming to operate across multiple asset classes and regions. Compared with traditional, hand-tuned strategies, DeepFin Research emphasizes scalable, ML-based systematic methods that can adapt to different markets and conditions. The goal is to improve investment decision-making and execution by deploying these models widely in the global markets.

Company size: 1-10
Company stage: Not listed
Total funding: Not listed
Headquarters: Jersey
Founded: 2022

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