Using APIs for Downstream Tasks

Suppose that you are a machine learning engineer for a large bank, working with the modeling team that creates input data for downstream models. Downstream models can include regulatory models for risk, internal models for credit decisions, internal risk models, marketing models, audits, and any other application where ML can be used.

You have access to the following APIs:

• Reddit API for all posts and comments for finance and news-related subreddits
• Bloomberg API for daily stock prices, including opening and closing prices

How would you go about designing an ML system that extracts data from those APIs, transforms the data, and stores it in a format that downstream modeling teams can use?