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10/25/2016
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Jessica Davis
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7 Data And Analytics Job Titles To Know

Leveraging data -- big and small -- has become a powerful tool for enterprise IT organizations that successfully transition to digital businesses. Opportunities within enterprise organizations have expanded to fill the need. Here's our list of job titles for today's data professionals.
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Data Scientist
Data scientist is the job title that's been getting lots of attention over the last few years, after Glassdoor named it the best career for work/life balance. Salaries are also relatively high. But what does it mean to actually be a data scientist?
Burtch Works defines data scientists as those who 'apply sophisticated quantitative and computer science skills to both structure and analyze massive unstructured data sets or continuously streaming data, with the intent to derive insights and prescribe action.' The executive recruiting firm says that the depth and breadth of these professionals' coding skills distinguishes them from other predictive analytics pros, and allows them to exploit data regardless of the source, size, or format.
These data pros often have a master's or a PhD in a quantitative discipline, such as applied mathematics or statistics, have expert knowledge of statistical and machine learning methods using tools such as R and SAS, according to Burtch Works. They are also usually proficient users of big data technologies such as Hadoop and Spark.
(Image: ismagilov/Stockphoto)

Data Scientist

Data scientist is the job title that's been getting lots of attention over the last few years, after Glassdoor named it the best career for work/life balance. Salaries are also relatively high. But what does it mean to actually be a data scientist?

Burtch Works defines data scientists as those who "apply sophisticated quantitative and computer science skills to both structure and analyze massive unstructured data sets or continuously streaming data, with the intent to derive insights and prescribe action." The executive recruiting firm says that the depth and breadth of these professionals' coding skills distinguishes them from other predictive analytics pros, and allows them to exploit data regardless of the source, size, or format.

These data pros often have a master's or a PhD in a quantitative discipline, such as applied mathematics or statistics, have expert knowledge of statistical and machine learning methods using tools such as R and SAS, according to Burtch Works. They are also usually proficient users of big data technologies such as Hadoop and Spark.

(Image: ismagilov/Stockphoto)

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