Data Analyst the majority at 61% with bachelors
Typical Field of Study:Statistics, Mathematics, Computer Science, Data Engineering.
Learn about the technical skills most in demand for this position.
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About Data Analyst
Yes, it is possible to work from home, most of the offers for Data Analyst are remote, because to carry out their functions they only need a stable and secure internet network. Some companies provide flexible hours to their employees, this helps employees to be able to work from home. manage your time.
Data analysts: Are in charge of extracting, grouping, processing data
Data scientists: Analyze data using statistics and machine learning techniques.
Data engineer: Has a more technical role, you design systems to work with data at scale.
Business analyst: Is characterized by analyzing data with the aim of developing projects and improvements in company processes
Financial analyst: Interprets financial data to provide strategies in terms of investment and profitability.
The highest salary for a Data Analyst is $119.000 USD and changes depending on the country in which you are working. Years of experience, your knowledge of probability and statistics, and your command of programming language, among other things, determine the average salary of a Data Analyst.
The lowest salary of a Data Analyst is $75.600 USD depending mainly on the demand at the moment and the projection into the future, also on the advances in technology, and the level of experience.
Companies usually choose professionals with a bachelor's degree in statistics and mathematics, and computer engineering, with very good experience in programming language and databases and Big Data.
SQL programming language, useful for communicating with other databases, allowing you to modify, organize, and store data
Statistical programming languages, to clean, analyze and visualize large data sets efficiently
Machine learning. Useful in building algorithms designed to find patterns in large data sets.
Great knowledge of Probability and statistics because they make it easy to identify patterns and trends in the data