Data scientists can expect to spend time using programming languages to sort through, analyze, and otherwise manage large chunks of data. Popular programming languages for data science include: Python, R, SQL, SAS
Being able to create charts and graphs is a significant part of being a data scientist. Familiarity with the following tools should prepare you to do the work: Tableau, PowerBI, Excel
Incorporating machine learning into your work as a data scientist means continuously improving the quality of the data you gather and potentially being able to predict the outcomes of future datasets.
Some employers may want to see that you have some familiarity grappling with big data. Some of the software frameworks used to process big data include Hadoop and Apache Spark.
The most brilliant data scientists won’t be able to affect any change if they aren’t able to communicate their findings well. The ability to share ideas and results verbally and in written language is an often-sought skill in data scientists.
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