Research Jobs in Web3

In 2023, IMC acquired Altas Technologies, a rapidly growing algorithmic trading firm with the ambition of creating tomorrow’s most technically advanced trading stack. By combining Altas’ highly advanced trading strategies with IMC’s execution and scaling capabilities, this move strengthens IMC's position in the market and is an important step towards ensuring stability and long-term growth for the firm.

At Altas Technologies we build robust, fully automated systems to predict and trade cryptocurrency markets and are in the process of extending our trading capabilities from crypto to global equity markets. You’ll join at a very exciting time in the growth of the team, and will be able to contribute to our success in scaling the strategy beyond crypto to the equities markets. As a technology-oriented and scientifically-minded group, we design and build our own cutting-edge systems, from high-performance trading platforms to large-scale data analysis and research infrastructure.

Your Core Responsibilities

As a Trading Researcher, you will be operating as a senior and core member of our high-performance, dedicated, multi-disciplinary team, with a background in Mathematics, Physics, Computer Science, Robotics, Data Science, Engineering, Statistics. The one thing we all have in common, regardless of our individual backgrounds, is a creative and scientific mindset.

You will not get a lot of top-down instruction telling you exactly what to do and when to do it. You'll get directional advice, useful frameworks, access to interesting challenges, and plenty of freedom to execute as you see fit. We are meritocratic by nature and believe that empowering talent in our organization is the only way to achieve our highly ambitious goals.

We are looking for a creative scientifically minded individual who can lead the growth of the firm’s trading research to improve execution quality in delta 1 mid-frequency (intraday) trading context. As a Trading Researcher, you will work together with the engineering team to implement and test execution improvements, and the research team to improve the strategies' capacity and profitability from the perspective of trading costs.

• You will have full ownership of the design and development of models and algorithms responsible for trading and optimal execution of billions in monthly volume
• You will work together with peer trading researchers and to analyze order book/trades data for execution models, and will work closely with quant research to develop trade cost models.
• Analyze large orders- and trades datasets for post-trade analytics, and improve monitoring capabilities to ensure we are always on top of the market, decomposing PnL and identifying blind spots / opportunities in the algorithms.

Your Skills and Experience

• An advanced degree with excellent grades in Mathematics, Physics, Computer Science, Data Science, Engineering, Statistics or any other highly quantitative field
• Experience as a Researcher in (high to mid-frequency) D1 execution research, ideating trades- and book features that are predictive of execution costs and short-term price movements.
• Significant practical experience with large messy datasets, including raw unstandardized equities data and the requisite pre-processing steps such as corporate action adjustments.
• Understanding of position management, market risk, and the optimal execution side of quant strategies (implementation shortfall, trade cost modelling).
• Scientific mindset with experience in data analysis with Python & any SQL dialect. Strong eye for detail and highly structured, using a rigorous process to ensure results are reliable and well tested
• Serious about clean code, simple but well-architected systems, and continuous improvement
• Sense of ownership taking full responsibility and accountability for your contributions
• Technical accomplishments are considered a plus: Kaggle, Hackathons, Olympiads, publications