We are partnering with a leading crypto trading firm to hire an Quantitative Modeler / Quantitative Researcher to build and scale systematic trading strategies across global digital asset markets.
Responsibilities
1. Strategy Research & Modelin
- gConduct quantitative strategy research and development across multiple asset classes, including equities, futures, options, convertible bonds, and ETFs. Strategy scope includes but is not limited to multi-factor stock selection, event-driven strategies, statistical arbitrage, CTA strategies, and options volatility strategies
- .Identify effective alpha factors and alternative data sources, such as news sentiment, supply chain data, satellite imagery, and other non-traditional datasets, to build predictive signals
- .Develop portfolio optimization models, and conduct risk attribution, position management, and trade execution optimization
2. Data Engineering & Feature Engineerin
- gProcess large-scale high-frequency and daily market data, fundamental data, analyst forecast data, and alternative datasets to build high-quality, reusable modeling datasets
- .Apply machine learning, deep learning, and time series analysis techniques to develop predictive models and return forecasting models
3. Backtesting Framework & Live Deploymen
- tBuild rigorous backtesting frameworks to ensure objective and robust strategy evaluation, while controlling for common pitfalls such as overfitting, survivorship bias, and look-ahead bias
- .Work closely with the trading systems team to translate strategy models into production-ready algorithms, monitor live trading performance, and continuously iterate and optimize models
4. Research & Innovatio
- nStay up to date with the latest quantitative research and academic literature globally, and explore the feasibility of applying new methods, such as graph neural networks, reinforcement learning, and large language models, to quantitative strategy modeling
- .Regularly produce research reports and participate in internal strategy discussions and investment decision meetings
Requirements
1. Educatio
- nMaster’s degree or above in Mathematics, Physics, Computer Science, Financial Engineering, Statistics, Electrical Engineering, or other quantitative disciplines
- .PhD preferred. Graduates from top domestic or international universities are preferred
2. Technical Skill
- sSolid foundation in mathematics and statistics, with strong knowledge of probability, stochastic processes, time series analysis, and optimization theory
- .Proficient in Python, with hands-on experience using tools such as Pandas, NumPy, Numba, PyTorch / TensorFlow, and Scikit-learn
- .Familiar with mainstream factor libraries and research platforms such as WorldQuant Alpha and Qlib, as well as the logic behind building backtesting frameworks
- .Strong SQL skills, with experience handling TB-scale datasets. Experience with distributed computing frameworks such as Spark or Dask is a plus
- .Deep understanding of the market microstructure of A-shares, Hong Kong equities, U.S. equities, futures, and options is highly preferred
3. Work Experienc
- eAt least 3 years of experience in quantitative strategy research or related roles. For junior openings, outstanding PhD graduates or exceptional Master’s candidates may also be considered
- .Prior live trading experience or a proven track record of contribution to live strategies is preferred
- .Experience in factor mining and applying machine learning to live quantitative strategies is highly preferred
4. Personal Attribute
- sHighly sensitive to numbers, with strong logical thinking, independent research capability, and critical thinking skills
- .Results-oriented, able to remain rational and disciplined in fast-changing market environments
- .Strong teamwork and communication skills, with the ability to thrive in a high-intensity research environment
Preferred Qualification
- sStrong performance in recognized quantitative competitions such as the WorldQuant Challenge or finance-related Kaggle competitions
- .Proficiency in high-performance programming languages such as C++ or Rust, or experience with trading system development
- .Publications in top-tier conferences or journals in finance, quantitative research, or related fields
- .Practical experience in alternative data applications, including NLP, image recognition, or similar domains
pls send your profile to li@al-access.com and our consultant will contact you soon.
