How to Become a Data Scientist

A data scientist is someone who collects and analyzes data to draw conclusions. They do this by many methods. They can display the data in a graphical way, also known as “viewing the data.” This helps a user search for simple trends that are not apparent if the information is presented in hard numbers on a table.

Data scientists also create advanced algorithms to identify trends and convert data into something useful for a business or organization. Data science is the discipline of looking for meaning in mass data volumes. As such, extensive knowledge of math is needed for this position.

In many of the world’s most fast-expanding industries, data science is one of the most marketable competencies. In the decade between 2016 and 2026, the Bureau of Labor Statistics (BLS)  forecasts a 19% increase in economic growth for data science. This percentage is far beyond the rosiest predictions for the labor market as a whole. BLS promises it to be particularly influential in the future for those with backgrounds in genetics, finance, and computer science.

data scientist
Photo credit: @arora.abhi / medium.com

Education and Training to Become a Data Scientist

You can secure a prosperous, rewarding career as a data scientist through many different paths. Most of them start at the graduate level with a bachelor’s in data science, which can lead to positions such as a data visualization expert, managing analysts, and market research analysts.

Most students graduate from programs that also train statisticians and software engineers. Most students graduate in concentrations like business solution investigators, data scientists, and enterprise software analytics managers.

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Certifications will also boost your know-how and make you more marketable. Potential certifications include certified professional developers and certified Cloudera specialists: data scientist, EMC: data science associate, and SAS certified SAS Enterprise Miner 7 predictive modeler.

Data Science vs. Statistics: What Is the Difference?

Data science should not be confused with statistics. While these two areas incorporate similar abilities and share common goals, they are distinct in one specific way. The new field of data science is based heavily on the use of computers and technology. It accesses full database records, uses software to manipulate data, and digitally visualizes numbers.

In general, the statistics use established theories and focus more on the testing of hypotheses. This discipline has changed little over the last 100 years or more from a broad point of view, while data science has evolved with increasing computer use.

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Average Salary of a Data Scientist

According to Business Insider, due to the remarkably high level of career satisfaction, the data science profession is “the most effective job in the United States” as of 2018. Another reason is the high salary that can run deep into the six figures range that is associated with the profession.

According to salary research site Glassdoor, the average annual base pay for data scientists is $120,931 — and that’s not including the $11,772 in additional cash compensation the average data scientist receives.

data scientist

Conclusion

Data science is a specialty, and networks, job boards, and career platforms for recruitment are only accessible to them and companies which need their expertise. If you have a knack for numbers and are great with technology, this could be a great profession for you. For more scientist-related jobs, click here.

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