Data Engineer/Data scientist to work on the low latency/high frequency models of market microstructure.
True Alpha is a small crypto trading fund. We provide liquidity in the main crypto assets on the centralized exchanges (mainly in BTC and ETH).
I am looking for a capable python data engineer who could take ownership of our backtesting analytical suite. As we are in the HFT space the backtesting will require to build a matching engine and replay our signals versus the historical limit order book. This is a complex and time-consuming process so I need someone who could organize the process optimally both for data storage and processing. The tech stack we are using is AWS, Python, AWS supported databases for the storage.
Once ready, a matching engine becomes an 'oracle' - when given input parameters - it outputs a value of an objective function that we need to improve on. We could optimize this function in different settings - as a classical model of machine learning, as the RL problem or through some more flexible DL models. An ideal candidate will combine deep data engineering experience with machine learning one.
As an ideal candidate:
- You have commercial experience building data pipelines for big data applications in AWS setting. - You understand classical machine learning models. Experience and knowledge in any of the following: signal processing, quantitative finance, reinforcement learning will be a big plus. - You have masters or PhD in Math, Physics or CS. You can understand and improve on the existing state of the art research in market microstructure and high-frequency trading. - You are up for a challenge as finance is the 'hardest game in the world'.
About True Alpha
True Alpha is an Australian high-frequency trading startup. We provide liquidity in crypto perpetual futures and spot on the most liquid instruments BTC and ETH.