Data Science in Stock Market

Financial data is a large component of all electronic data. For example, an average stock exchange produces trillions of Gigabytes (G of trade and order book data in a month. So naturally, there are massive applications of machine learning and data science tools in the field of finance. 

The different components where Data Science is used in trading are-

Algorithmic Trading- Recommendation of a stock is a part of algorithmic trading, To understand and model these algorithms, one requires a strong background in the field of mathematics, statistics, programming, and finance. Gathering the data and doing a predictive analysis is done by various Data Science tools.
Financial Computing- Managing electronic data and making the data more and more optimized is a part of financial computing. For example, to provide pricing to a stock we require optimized simulated data from the company, this raw data is consolidated by data science tools which help to provide an estimation price of a stock.
Apart from the above, data visualization tool development, database management, etc are extra skills a data science person is expected to know.

https://intellipaat.com/blog/what-is-data-science/