I'm looking for a python expert who can run docker compose v 2.5 or greater on their computer.
we need to find high correlations between two 4-6 month time sereies samples aggregated from all stocks in time in the s&p 500
I represent a data science company and can provide you a few contracts.
please select a time here [login to view URL]
please have these answers during interview
1. are you quick with docker-compose and docker?
2. are you quick with python libraries such as pandas
3. do you python asynchronous or multiprocessing to speed up a thorough ranking analysis
4. what type of table do you need to find an aggregate correlation coefficient sum for a time in s&p so that we find the highest correlation between today and another bear market
5. learn this first [login to view URL]
6. do you know git and have a bitbucket account?
7. are you okay to earn a bonus for finishing this project in 2 weeks worth 25$
for ~41$ per milestone
1. function which returns data from db or online time series
1.1. particularly stock_name_for_embedding, date_for_embedding and ohlcv for each stock in the s&p 500
1.2. my current code base will make this easier
2. mycorrelation function which returns correlation coefficient for 2 time series parameters with same candle type and length in time series
3. create correlation_ranker(backwards_from_now=True, time_length, candle length) which returns a ranking of time series matches