Junior Quantitative Researcher

About BlockTech

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.

The role

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.

You will:

• 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

What we're looking for

• 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

What's in it for you?

• A seat on a trading floor where research, engineering, and trading happen a few metres apart, guaranteeing short feedback loops, real ownership, and direct impact on live PnL
• Competitive compensation consisting of a base salary combined with a very attractive bonus plan based on individual and company performance
• Outstanding performance is rewarded with the opportunity to buy into the trading fund
• Pension plan, company laptop, and reimbursement of your internet costs at home
• An extensive in-house training program and an annual learning & development budget
• The opportunity to work at the forefront of automated trading using state-of-the-art technology, in an environment that embraces AI to both accelerate productivity and advance our systems and models
• Gym membership reimbursement and the opportunity to engage in various sports during working hours, including kickboxing, CrossFit, fitness, and soccer
• Regular social events, including weekly Friday drinks, monthly outings, quarterly sports competitions and bi-annual trips abroad
• Daily breakfast and w