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We do: - 15min crypto options market-making - arbitrage with Binance - insider-identifying directional bets - mid frequency copy trading - to be continued…
We value tier-1 engineers and quants.
Our team: - worked in top tier high freq trading hedge funds (binance, okx, …) - made infrastructure for onchain data (solana, base, hyperliquid, …) - won IOI and kaggle competitions
We are ready to onboard 2 people to our team
Quant: research & improve strategies, backtest, reverse other traders
Engineer: making high performance data providers and trading engine
Nice to have some from you: - Top tier education - Understanding of MEV and onchain arbitrage/market-making - Experience in trading, crypto or traditional markets - Other relevant background
What we offer: - Top market salary and profit sharing - Unique and challenging tasks - Strong team and growth
We're looking for a Quant Researcher to join us remotely and take direct ownership of the research lifecycle, from raw data exploration all the way through to live strategy deployment. You'll work closely with our trading and engineering teams to develop, test, and continuously refine the models and algorithms that drive real P&L outcomes across crypto markets. This is a high-ownership role with meaningful exposure to live markets from day one. You won't be running support research in the background, you'll be a core contributor shaping the strategies we actually trade. That means working with large and often unconventional datasets, identifying exploitable statistical patterns in volatile and illiquid market conditions, and translating rigorous mathematical research into production-ready code that performs when it counts. Responsibilities Develop, backtest, and continuously improve quantitative trading models and algorithms, translating mathematical insights into production-ready code Collaborate with trading and development teams to refine existing strategies and build new ones with a direct focus on P&L impact Work through large and complex datasets to identify patterns, validate hypotheses, and stress-test models against real market conditions Conceptualize valuation frameworks, improve mathematical models, and maintain strategy performance in live environments Conduct ongoing statistical research into crypto market microstructure and price dynamics using both conventional and unconventional data sources
Requirements Advanced degree in mathematics, statistics, physics, computer science, or a related quantitative field Strong proficiency in probability and statistics, including time-series analysis, machine learning, and pattern recognition applied to financial data Hands-on programming experience in Python, with familiarity in R or MATLAB and ideally some exposure to compiled languages like C++ Prior experience in crypto markets, digital asset trading, or algorithmic finance Proven ability to work in a data-driven research environment with minimal direction Rigorous, evidence-based approach to problem-solving with the ability to move quickly from hypothesis to testable implementation
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