Quantitative Researcher

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We are seeking a skilled Quantitative Researcher to join our team in developing advanced algorithmic trading strategies for cryptocurrency markets. You will leverage deep quantitative skills, market insights, and statistical modeling to research, design, and test trading strategies that capture alpha in digital asset markets.

• Research and develop quantitative trading strategies for crypto markets across spot, perpetual futures, and derivatives.
• Analyze market microstructure, order flow, and liquidity to identify trading opportunities.
• Design and implement statistical and machine learning models for signal generation, risk forecasting, and anomaly detection.
• Perform extensive backtesting, simulation, and performance analysis using historical and live data.
• Optimize strategies for execution costs, slippage, latency, and market impact.
• Collaborate with developers to translate research into production-grade algorithmic trading systems.
• Monitor live strategies and conduct post-trade analysis to refine and improve models.
• Stay updated on market trends, blockchain analytics, protocol updates, and evolving market structure.
• Contribute to research documentation, strategy reports, and knowledge sharing within the team.

• Strong background in quantitative research, statistical modeling, or applied mathematics.
• Solid programming skills in Python, R, or similar languages for data analysis and prototyping.
• Experience with time series analysis, signal processing, and statistical inference.
• Ability to work with large datasets; proficiency in data cleaning, feature engineering, and data visualization.
• Understanding of trading concepts such as PnL attribution, Sharpe ratio, drawdown, and risk management.
• Interest in cryptocurrency markets and familiarity with crypto-specific market dynamics.
• Excellent problem-solving and critical-thinking skills.
• Ability to communicate complex quantitative ideas clearly to technical and non-technical stakeholders.

• Prior experience in algorithmic trading or systematic strategy development (crypto or traditional markets).
• Knowledge of crypto market microstructure, DeFi protocols, and blockchain data analytics.
• Familiarity with exchange APIs, order types, and execution logic.
• Experience with backtesting frameworks and simulation environments.
• Machine learning experience applied to financial markets (e.g. feature selection, ensemble models, reinforcement learning).
• Academic background in quantitative disciplines (e.g. Mathematics, Statistics, Physics, Computer Science, Engineering, Finance).