Image: Top 20 technology skills in data scientist job listing
Nowadays, Python is the most common programming tool used by Data Scientists. It is a great programming tool that most companies will need along C++/C and Java.
Python is beginner friendly and has a large community of users.
Python is very convenient in the way it is useful for every step of data science processes.
It can also integrate various forms of Data and it is easy to import SQL into Python Code. Finally, you can put in place a large number of datasets by searching on Google.
Before Python become the most demanded skill by recruiters, R was in first place. Still, it is today a must-have in your tool belt. R is a programming language designed for Data Scientists and Statisticians.
This is not an easy programming tool to start with because this is mostly used for. But it is a great tool for every aspiring Data Scientists.
SQL (Structured Query Language) is a programming language designed to add, delete and extract data.
This is the primary way to interact with the relational database. It can also help you to carry out a series of problems. A lot of employers need data scientists to be able to write and execute complex queries on SQL. This is definitely a skill to prove during a Data Scientist interview.
Hadoop and Spark are two tools designed by Apache for Big Data. Hadoop is not required as much as C/C++, Python, Java or Perl. But, it is a skill that a lot of Data Scientists also have.
Why? Because Hadoop will be the best tool to use when you need to deal with a large amount of data.
Hadoop ecosystem is also a great tool for such tasks as data exploration, data filtration, data sampling, and data summarization.
Spark, like Hadoop, is a big data computation framework. The difference with Hadoop is that Spark is faster. That’s why this is the most Big Data Technology worldwide.
It will be particularly useful to help run complicated algorithms faster
Data Scientist also uses Spark when they have to handle unstructured data sets. Finally, Spark is famous because it makes easy to carry out data science projects.
Java is a flexible and universal programming language. It has an extensive library of APIs. This language is very useful when it come to use Java code on new programming software such as Python.
It requires less processing and RAM than other programing languages. It is very versatile, universal and reliable.
Finally, it has evolved with surrounding technology / allowing the language to adapt tech application needs as they have developed
From the Guide: Data Scientist Job: Role, Skills, Education, Tools and Salary