paired time series correlation

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