Quantitative Researcher

BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems.

Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. 

We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further.

As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction, through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. 

You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade.

• Collaborating closely with traders to translate research insights into systematic trading strategies

• Designing, developing and deploying models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques.

• Building robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely

• Owning models in production: monitoring live performance, diagnosing decay, and iterating on what you ship

At our core, we are a team of passionate trading and tech enthusiasts committed to revolutionizing trading through automation. Our collaborative approach ensures that everyone contributes to achieving our ambitious goals.

In this role, you will be both challenged and stretched, with ample opportunities for growth and development, both within and beyond your main responsibilities.

We invest in our people by offering competitive compensation and benefits, fostering innovation, and celebrating success. Our commitment to personal development transcends traditional norms; we provide an equal playing field, promote reverse leadership, and offer boundless growth opportunities for all our employees.

Join us to unlock your potential and drive innovation in the exciting world of algorithmic trading.

• A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience

• Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas)

• A deep, intuitive grasp of overfitting, generalisation, validation design, and feature engineering - you can explain why a model works, not just that it does

• Solid software engineering instincts: you write code that other people can read, test, and run in production

• Genuine curiosity about financial markets and market microstructure - prior finance experience is welcome but not required

• Clear written and verbal English, and the ability to communicate complex ideas to a mixed audience of researchers, engineers, and traders

Nice to have

• Hands-on experience building and deploying ML models, ideally on time-series, forecasting, or anomaly detection problems

• Familiarity with crypto markets, derivatives pricing, and/or high-frequency trading data