Job Title: Quantitative Researcher Location : Remote (Europe or Asia Timezone) Job Type : Full-time, 12-month contract with an initial 3-month probationary period Compensation : Hourly, highly competitive, based on experience Company Overview : We are a proprietary trading firm leveraging cutting-edge technology to build the foundation for our market-making activities in crypto derivatives. Our focus is on developing quantitative models for price forecasting, volatility forecasting, and optimal quoting strategies. We are looking for a Quantitative Researcher with 2 years of professional experience to help drive the development of these models. This role offers the chance to work in a dynamic environment while growing your expertise in advanced quantitative finance. Key Responsibilities: Volatility and Price Forecasting : Design and implement time series models for price and volatility forecasting, including ARIMA and GARCH and integrate them into real-time trading systems. Volatility Surface Modeling : Build and calibrate volatility surface models (e.g., SVI, SABR) to improve quoting strategies and risk management. Market Making Optimization : Create algorithms to optimize bid-ask spreads in market making, based on real-time volatility, liquidity, and market dynamics. Backtesting & Validation : Perform rigorous backtesting of models on historical data to ensure robustness and suitability for live trading. Data Handling : Work with large, streaming intraday data to generate real-time signals for volatility and price forecasting. Future Contributions to Machine Learning : While machine learning is a future project, there is potential to contribute to models like LSTM, reinforcement learning, and sentiment analysis for enhanced forecasting. Key Qualifications: Qualifications: A Masters degree in a quantitative field, or a Bachelors degree combined with substantial, relevant professional experience. Experience : Minimum of 2 years of professional experience in quantitative finance Quantitative Expertise : Strong foundation in time series analysis, including ARIMA, GARCH for volatility forecasting, and SABR for volatility surfaces. Programming Skills : Strong skills in Python, with knowledge of modules using time-series analysis and NLP. Financial Knowledge : A strong understanding of derivatives pricing, volatility surfaces, and options Greeks, especially in the context of crypto markets. Real-Time Systems : Experience developing and deploying models in real-time, low-latency trading systems. Preferred Skills: Familiarity with KDB/q is highly desirable for managing large real-time datasets and optimizing model deployment. Familiarity with crypto markets and exchange dynamics. Knowledge of machine learning techniques is a plus for future projects. Why Join Us: This role is ideal for someone looking to further develop their skills in quantitative finance, while contributing to foundational models for a growing crypto market-making firm. Competitive pay with performance-based bonuses. Flexible remote work environment, with opportunities for future contributions to machine learning projects.