The Difference Between Data Analysts and Data Scientists

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11 January 2017

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The terms “data analyst” and “data scientist” are often used interchangeably, as both jobs are critical when it comes to analyzing corporate data in meaningful ways. However, the jobs themselves are actually quite distinct. Each comes with different responsibilities and each job title requires unique qualifications. So just what are the differences between the two?

What is a Data Analyst?

Data analysts are tasked with collecting, manipulating, and of course, analyzing data. They take that data and prepare reports which detail their results.  Analysts are also responsible for guarding and protecting the data they work with.  Data analysts almost always hold bachelor’s degrees, and many have master’s degrees in business intelligence specializations.   If they continue their education, many data analysts move on to become data scientists.

Data Analysts

According to Glassdoor, the median salary for data analysts in the United States is $60,000. Salaries range from $43,000 on the low end to $86,000 on the high end.

The skills and qualifications of data analysts typically include:

  • A solid understanding of data stuctures
  • A solid understanding of BI concepts
  • Experience with SQL
  • Experience with Hadoop platforms
  • Familiarity with ETL tools
  • Schema design
  • Data architecture

Data Scientists

Data scientists hold master of science and PhDs in subjects like math, statistics, operations research, or machine learning.  They also go a step beyond technical expertise, and many also hold MBAs. Why? Strong business acumen is required in order to effectively address business problems. Data scientists have to be able to communicate their findings with IT leaders and other non-technical business leaders, as their work influences the way an organization makes decisions and approaches problems.

According to Glassdoor, the median salary for data scientists in the United States is $115,000, with salaries ranging from $80,000 on the low end to $146,000 on the high end. The level of education factors into higher compensation levels.

The skills and qualifications of data scientists typically include:

  • Familiarity with SQL
  • Expertise in analytics functions (median, rank, over, etc.)
  • Predictive modeling and analytics skills
  • Math, statistics, and correlation expertise
  • Data mining
  • Excel, SAS, MATLAB experience
  • Extensive experience working with extremely large data sets and visualization

The individual needs of the organization often dictate the exact skills required of their data scientists. Industry-specific expertise is very important, and most data scientists typically focus on one specialty throughout their careers.

If you are a data analyst or a data scientist looking for new opportunities, contact OnBoard Recruitment Advisers today. We specialize in analytics and data-related positions in a variety of fields, and we can help connect you with the right opportunity to take your career to the next level.

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