Cumberland - a DRW Company, is the cryptoasset arm of DRW, established in 2014 after pursuing an early interest in cryptoassets and their underlying technologies. Today, Cumberland is a global leader in cryptoassets, uniquely positioned between the traditional financial markets and the cryptoasset ecosystem. From our offices in Chicago, London and Singapore, Cumberland provides 24-hour access to a wide array of cryptoassets while helping the crypto ecosystem evolve in a responsible, sustainable way.
We are currently seeking a Quantitative Researcher to join our team in Singapore. As a Quantitative Researcher, you will develop mathematical models using advanced statistical learning methods to build automated trading strategies for cryptoassets. Our research team collaborates on idea generation and strategy development, while encouraging independent exploration and original approaches. You will conduct quantitative analysis of market data to uncover relationships and identify historical trends.
How you will make an impact
- Extract predictive signals from financial data through both traditional statistical analysis methods and cutting edge machine learning techniques
- Assist software developers to translate research strategies into production software
- Optimize the order execution and risk management of our trading system
- Create robust solutions to problems presented in the trading environment
- Formulate and apply mathematical modeling techniques to enhance existing trading strategies and perform innovative new research with the goal of identifying and capturing trading opportunities
- Automate human-decision based trading strategies; prototype algorithmic trades from trading ideas
You will be right at home if you have…
- A degree in a technical discipline with a focus on statistics, machine learning, signal processing, optimization and control.
- Min. 2 years of research experience within the cryptoassets industry
- A curiosity for model development and experience handling large data sets
- Expertise in programming using Python, R, MATLAB, or C++ for conducting research
- Can advocate for your beliefs in a concise and effective way with the team
- Significant hands-on experience applying machine learning algorithms to real world problems
- Strong problem-solving and statistics skills
- The proactive ability to take the lead on assignments and deliver practical research results in a timely manner
