My client is a one-of-a-kind quantitative trading company operating on the cutting edge of technology. The company has risen to prominence in the HFT space in recent years, by leveraging not only the expertise of their talented people, but also state-of-the-art research infrastructure. Trading activities span various platforms worldwide, encompassing both traditional and cryptocurrency markets.
Now seeking a strong Quantitative Researcher to join the team, where you will be involved in both research and trading. Your day-to-day will include:
- Operate automated latency-sensitive trading systems
- Monitor the systems’ executions and open positions
- Adjust system parameters based on market conditions
- Manually trade to reduce risk when necessary
- Suggest automation and improvements to the systems
- Communicate relevant news, market events, and system behavior to team members
- Stay current with system functionality
They operate within a truly flat organizational structure, not siloed like other firms. You can work from anywhere in the world, or in one of their fully equipped offices if you prefer.
Requirements
- 3+ years of algorithmic trading experience
- A proven track record in the last 2-3 years
- Having your own trading strategies/ideas
- 1+ year of experience in Python
- Performs well in a remote/hybrid team with variable, project-based responsibilities
Nice to have
- Experience with international HFT companies and hedge funds
- Strong competitive/technical background: performance in any quantitative field or contest (hackathons, Olympiads, academic contests, etc.) highly beneficial
Benefits
- Complex challenges with fast feedback loops
- Great corporate culture with internal events & commitment to fostering a supportive and empowering environment
- Cutting-edge hardware and technology
- Flexible schedule
- Significant paid days off
- Competitive salary and performance-based bonuses
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.