A lot of that is relevant to machine learning engineer jobs, especially time series modeling, reinforcement leaning, databases, and real time systems, so highlight those areas if you apply to ML eng jobs.
The more detailed you can be, the more "real" your job experience will look. For example, list the time series algorithms you used and quantity how they helped (error metrics, % return, comparison to a naive forecast, etc). I already mentioned latency. Optimizing your code and data for speed is something interesting you could get into too.
- real time trading system on orderbook level
- market research and visualisation
- timeseries modelling with different algorithms
- research different approaches, like reinforcement learning for trading
- database design and optimization. Currently the database has 42 billion entries
- web3 coding with solidity
- software architecture
- logging, don't lough. Huge part. Very hard to implement.
How did I beat the competition:
- was quicker than any one else.
- Also guess had more clever strategies, but it is hard to get into the details.