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The differences between product analysts and data scientists can be seen in a few details. Each job has different responsibilities and duties. It typically takes 2-4 years to become both a product analyst and a data scientist. Additionally, a data scientist has an average salary of $106,104, which is higher than the $79,316 average annual salary of a product analyst.
The top three skills for a product analyst include tableau, data analysis and product management. The most important skills for a data scientist are python, data science, and visualization.
| Product Analyst | Data Scientist | |
| Yearly salary | $79,316 | $106,104 |
| Hourly rate | $38.13 | $51.01 |
| Growth rate | 11% | 16% |
| Number of jobs | 176,369 | 106,973 |
| Job satisfaction | - | - |
| Most common degree | Bachelor's Degree, 73% | Bachelor's Degree, 51% |
| Average age | 44 | 41 |
| Years of experience | 4 | 4 |
A product analyst job utilizes data analysis software and notates trends in market research. Primarily, analysts project the costs of product development and marketing. They think of the possibilities for profit and sales and monitor the performance of products on the market to come up with a better product. Their responsibilities include company product evaluation, product understanding, and product rating reviews. Familiarity with Microsoft Office Suite, strong communication skills, and proficiency in database software is necessary for this job.
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.
Product analysts and data scientists have different pay scales, as shown below.
| Product Analyst | Data Scientist | |
| Average salary | $79,316 | $106,104 |
| Salary range | Between $56,000 And $111,000 | Between $75,000 And $148,000 |
| Highest paying City | Seattle, WA | Richmond, CA |
| Highest paying state | Washington | California |
| Best paying company | Meta | The Citadel |
| Best paying industry | Technology | Start-up |
There are a few differences between a product analyst and a data scientist in terms of educational background:
| Product Analyst | Data Scientist | |
| Most common degree | Bachelor's Degree, 73% | Bachelor's Degree, 51% |
| Most common major | Business | Computer Science |
| Most common college | University of Georgia | Columbia University in the City of New York |
Here are the differences between product analysts' and data scientists' demographics:
| Product Analyst | Data Scientist | |
| Average age | 44 | 41 |
| Gender ratio | Male, 53.2% Female, 46.8% | Male, 79.6% Female, 20.4% |
| Race ratio | Black or African American, 7.6% Unknown, 4.5% Hispanic or Latino, 8.5% Asian, 14.6% White, 64.6% American Indian and Alaska Native, 0.2% | 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 | 12% | 9% |