Quantitative Researcher
AI Summary
About BlockTechBlockTech 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.
About this role
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.
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.
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.
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
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
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