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The differences between data specialists and data scientists can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 1-2 years to become a data specialist, becoming a data scientist takes usually requires 2-4 years. Additionally, a data scientist has an average salary of $106,104, which is higher than the $68,326 average annual salary of a data specialist.
The top three skills for a data specialist include data analysis, data entry and data collection. The most important skills for a data scientist are python, data science, and visualization.
| Data Specialist | Data Scientist | |
| Yearly salary | $68,326 | $106,104 |
| Hourly rate | $32.85 | $51.01 |
| Growth rate | 9% | 16% |
| Number of jobs | 100,301 | 106,973 |
| Job satisfaction | - | - |
| Most common degree | Bachelor's Degree, 56% | Bachelor's Degree, 51% |
| Average age | 44 | 41 |
| Years of experience | 2 | 4 |
A data specialist's role is to process data, transferring them into an electronic platform or database for record-keeping or creating systems. Their primary responsibility is to ensure the accuracy of every inputted data point and verify its authenticity by reaching out to clients or using specific software. There are also instances when they must perform various analyses or take part in different product development processes. Furthermore, it is crucial to be able to identify any anomalies or inconsistencies; this way, corrective measures can be quickly implemented.
A Data Scientist analyzes information from multiple sources in order to gain maximum insight that can give the company a competitive advantage. They work in different domains, including manufacturing, healthcare, education, and finance.
Data specialists and data scientists have different pay scales, as shown below.
| Data Specialist | Data Scientist | |
| Average salary | $68,326 | $106,104 |
| Salary range | Between $40,000 And $116,000 | Between $75,000 And $148,000 |
| Highest paying City | San Francisco, CA | Richmond, CA |
| Highest paying state | Connecticut | California |
| Best paying company | McKinsey & Company Inc | The Citadel |
| Best paying industry | Manufacturing | Start-up |
There are a few differences between a data specialist and a data scientist in terms of educational background:
| Data Specialist | Data Scientist | |
| Most common degree | Bachelor's Degree, 56% | Bachelor's Degree, 51% |
| Most common major | Business | Computer Science |
| Most common college | - | Columbia University in the City of New York |
Here are the differences between data specialists' and data scientists' demographics:
| Data Specialist | Data Scientist | |
| Average age | 44 | 41 |
| Gender ratio | Male, 40.6% Female, 59.4% | Male, 79.6% Female, 20.4% |
| Race ratio | Black or African American, 9.6% Unknown, 4.3% Hispanic or Latino, 19.5% Asian, 9.9% White, 56.0% American Indian and Alaska Native, 0.6% | Black or African American, 4.2% Unknown, 5.4% Hispanic or Latino, 6.9% Asian, 18.8% White, 64.2% American Indian and Alaska Native, 0.6% |
| LGBT Percentage | 5% | 9% |