Quantitative Researcher

A one-of-a-kind international company operating on the cutting edge of technology. The company has risen to prominence in the HFT (High-frequency trading) industry in recent years, having built one of the greatest teams of developers and data scientists on the market, including a great machine learning expert and top-level data scientist as the company's founder. Our trading activities span across various platforms worldwide, encompassing both traditional and cryptocurrency markets. We are seeking a Quantitative Researcher with a minimum of 3 years of experience in algorithmic trading. The one who embodies intelligence, calmness, and composure. We have a lot of financial data, robust infrastructure, and a highly skilled professional team. WHAT YOU’LL BE DOING: 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 WHAT WE LOOK FOR IN YOU: 3+ years of algorithmic trading experience A proven track record in the last 2-3 years Having your own trading strategies/ideas 1+ years 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 Performance in any quantitative field or contest (hackathons, Olympiads, academic contests, etc.) WHY SHOULD YOU JOIN OUR TEAM? Great challenges with fast feedback loops A welcoming group of highly qualified international professionals Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment Cutting-edge hardware and technology Work remotely from anywhere in the world Access any of our global offices anytime Flexible schedule 40 paid days off Competitive salary and performance-based bonuses