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A cutting-edge trading firm is seeking a Quantitative Researcher to design and deploy strategies in high-frequency trading environments. The role involves analyzing market data, creating predictive models, and collaborating with engineering teams. Candidates should have an advanced degree in a quantitative field and experience in HFT. This is a fully remote position that values innovation and results over location.
At OctoHorizon, we are pioneering advanced algorithmic strategies in the world of high-frequency trading (HFT). Our team of quantitative researchers and engineers pushes the boundaries of digital exchange trading through mathematical precision, cutting-edge infrastructure, and speed-focused innovation. We specialize in identifying ultra-short-term inefficiencies across markets by combining deep quantitative research with high-performance technology.
We offer a flexible, fully-remote environment built on merit, autonomy, and excellence — empowering top talent around the globe to contribute meaningfully to real-world trading strategies.
We are seeking an exceptional Quantitative Researcher to design, test, and deploy alpha-generating strategies across high-frequency trading environments. In this role, you will analyze microstructure data, build short-horizon predictive models, and collaborate with engineers to implement low-latency strategies on live markets. You will be expected to think rigorously, iterate quickly, and adapt strategies to ever-evolving market conditions.
This is a fully remote position, open to candidates globally. We prioritize results and innovation over location and time zones.
Research and develop high-frequency, alpha-generating trading strategies.
Analyze order book and tick-by-tick market data for patterns and anomalies.
Model price dynamics, liquidity, and volatility on sub-second horizons.
Design, implement, and backtest strategies with realistic execution constraints.
Collaborate with engineering to deploy models in production systems with low-latency requirements.
Evaluate strategy performance in live markets; diagnose and resolve anomalies.
Create tools for real-time monitoring, feature generation, and data analytics.
Continuously optimize for execution speed, model robustness, and scalability.
Advanced degree (MSc/PhD) in a quantitative field (Mathematics, Statistics, Physics, CS, Engineering).
Proven experience in high-frequency trading or ultra-low-latency algorithmic research.
Expertise in quantitative modelling, statistical analysis, and predictive analytics.
Deep understanding of market microstructure, order flow, and execution mechanics.
Programming skills in Python (for research and prototyping), plus proficiency in C++.
Experience working with high-volume, high-frequency datasets.
Ability to work independently in a fully remote, fast-paced environment.
Prior experience in live deployment of HFT or ultra-short horizon trading strategies.
Familiarity with crypto, FX, equities, or futures markets.
Knowledge of latency arbitrage, co-location strategies, or execution algorithms.
Publications, Kaggle rankings, or open-source contributions in relevant fields.
Fully remote role – work from anywhere in the world.
High-impact environment – your work directly affects PnL and strategy performance.
Access to world‑class data, tools, and infrastructure.
Collaborative, flat team structure with high autonomy.
Competitive compensation, including performance‑based bonuses.
Intellectual freedom to explore, research, and innovate.
If you are passionate about markets, mathematical modeling, and speed — and want to work on real strategies in real time — we’d love to hear from you.
Submit your CV, along with a short cover letter or portfolio highlighting your most relevant work.
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