Quantitative Researcher

About 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.

Responsibilities

• 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

Requirements

• 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
• 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 is in it for you?
• A permanent full-time position in a relaxed and trendy office located in the heart of Singapore's financial district (CBD)
• Competitive compensation consisting of a base salary combined with a very attractive bonus plan based on individual and company performance
• Additionally, outstanding performance is rewarded with the opportunity to buy into the trading fund
• 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
• Laptop, home office budget and transportation allowance
• Daily breakfast and warm lunch. Additionally, snacks and drinks are provided throughout the day
• Reimbursement of gym membership, sports events and the opportunity to do sports during working hours
• Regular social events, including bi-annual trips abroad and frequent outings
• For internationals: All-in relocation package
• Our culture
• 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.
• Join us to unlock your potential and drive innovation in the exciting world of algorithmic trading.

Additional Information

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.

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