Quant Researcher

About the Firm

Our client is a high-performing proprietary trading firm specialising in digital assets. The firm deploys quantitative and algorithmic strategies, supported by rigorous data-driven research and disciplined risk management. Alongside trading, its ventures arm selectively invests in high-potential projects shaping the future of digital markets.

About the Role

Our client is seeking a Quantitative Researcher with strong statistical intuition and a demonstrated ability to generate real PnL. This role sits close to capital. Your research will move from hypothesis to production and directly influence live trading, risk allocation, and portfolio construction across digital asset markets.

This is not an academic role. Signal quality, robustness, and monetization matter.

What You’ll Do

• Design, test, and deploy quantitative trading models using statistical, econometric, and machine-learning techniques.

• Own the full research lifecycle from idea generation to live PnL attribution.

• Analyze diverse datasets including market microstructure, derivatives, on-chain data, and macro signals to identify durable alpha.

• Run rigorous backtesting, stress testing, and post-trade analysis to understand drivers of performance.

• Partner closely with other researchers and engineers to productionize models and improve research and execution infrastructure.

• Continuously refine strategies based on empirical results and changing market regimes.

What We’re Looking For

• 2+ years of experience in quantitative research or systematic trading at a hedge fund, prop trading firm, or similarly research-driven environment.

• Clear evidence of PnL impact, either through standalone strategies or meaningful contributions to larger systems.

• Strong programming skills in Python or a comparable language, with experience handling large, noisy, or high-frequency datasets.

• Solid understanding of statistical modeling, forecasting, and machine-learning methods used in trading.

• Genuine interest and hands-on experience in crypto, blockchain, or digital asset markets.

• High ownership mindset. Comfortable operating in fast-moving environments where research decisions directly affect capital.

Why This Role

• Direct line between research and capital deployment.

• Exposure to liquid crypto markets with meaningful inefficiencies.

• High autonomy, high expectations, and strong upside for people who deliver.