Contek is a quantitative trading firm specialising in the blockchain sector. Our trading strategies are built on a foundation of rigorous scientific research, complemented by our in-house development of cutting-edge trading technologies and systems. Its core members are graduates from prestigious institutions such as Tsinghua University, Oxford and Imperial College London, etc, and have previous experience working at hedge funds (WorldQuant, GSA Capital, Jump Trading, etc) and technology companies (Google, Facebook, Microsoft, etc).
The founding team began trading cryptocurrencies in early 2017 and, over a span of six years, has developed a profound understanding of market structures and blockchain technology. Compared to teams with traditional financial backgrounds, we excel at identifying unique alpha and trading opportunities in the cryptocurrency market.
Work type: Internship, having opportunities to turn permanent
Location: Shenzhen, Shanghai
Quantitative Researcher as part of a small, collaborative trading team with a focus on systematic trading strategies in cryptocurrency markets.
Organize and analyze high-frequency order book/trade data to extract key features, and collaborate with developers to synthesize mid- and low-frequency data.
Develop intraday and mid-to-low-frequency predictive factors based on data.
Collaborate with the development team to design and build research tools and platforms, improving factor generation, testing, and optimization processes.
Participate in the design and construction of factor evaluation frameworks, connect with modeling/backtesting systems, and validate factor performance.
Conduct in-depth research on cryptocurrency risk models and develop risk factors using existing datasets.
Model and forecast liquidity, volatility, and other potential risks to improve real-time portfolio risk management.
Bachelor’s degree or above from top domestic universities (985) or renowned overseas institutions, in Mathematics, Physics, Computer Science, or related STEM discipline
Solid foundation in mathematics, linear algebra, and statistics, with strong understanding of probability theory and statistical analysis methods.
Independent research experience in big data processing and statistical analysis, with familiarity in common data processing techniques and methods.
Proficiency in Python, along with data analysis libraries such as NumPy, Pandas, and Scikit-learn.
Understanding of machine learning models such as LightGBM, RNN, and LSTM; familiarity with genetic algorithms.
Publications in renowned journals or conferences in Statistics, Applied Mathematics, Computer Science, or related fields.
Working experience in Quantitative Trading Firms.
Awards in mathematics or physics competitions.
Competitive remuneration package and a meritocratic culture where accomplishments are rewarded
Dynamic and result-driven with a flat structure
Collaborative teams in an energetic and casual working environment
Excellent exposure to the crypto ecosystem and the latest market insight