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The differences between clinical statistical programmers and data scientists can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 6-8 years to become a clinical statistical programmer, 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 $83,894 average annual salary of a clinical statistical programmer.
The top three skills for a clinical statistical programmer include macro, data management and adam. The most important skills for a data scientist are python, data science, and visualization.
| Clinical Statistical Programmer | Data Scientist | |
| Yearly salary | $83,894 | $106,104 |
| Hourly rate | $40.33 | $51.01 |
| Growth rate | -7% | 16% |
| Number of jobs | 77,290 | 106,973 |
| Job satisfaction | - | - |
| Most common degree | Bachelor's Degree, 59% | Bachelor's Degree, 51% |
| Average age | 47 | 41 |
| Years of experience | 8 | 4 |
Clinical statistical programmers collect data, execute statistical analysis, and analyze data sets based on the needs of the clients or employers. The programmers use SAS programming for data set development and analysis during clinical trials. They integrate data for reports after statistical analysis or clinical research. The skills they need to develop include analytical thinking, attention to detail, research, and strategic planning. They should also need to know statistical programming in clinical research.
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.
Clinical statistical programmers and data scientists have different pay scales, as shown below.
| Clinical Statistical Programmer | Data Scientist | |
| Average salary | $83,894 | $106,104 |
| Salary range | Between $59,000 And $117,000 | Between $75,000 And $148,000 |
| Highest paying City | San Francisco, CA | Richmond, CA |
| Highest paying state | New Hampshire | California |
| Best paying company | Genentech | The Citadel |
| Best paying industry | Retail | Start-up |
There are a few differences between a clinical statistical programmer and a data scientist in terms of educational background:
| Clinical Statistical Programmer | Data Scientist | |
| Most common degree | Bachelor's Degree, 59% | Bachelor's Degree, 51% |
| Most common major | Statistics | Computer Science |
| Most common college | Columbia University in the City of New York | Columbia University in the City of New York |
Here are the differences between clinical statistical programmers' and data scientists' demographics:
| Clinical Statistical Programmer | Data Scientist | |
| Average age | 47 | 41 |
| Gender ratio | Male, 67.0% Female, 33.0% | Male, 79.6% Female, 20.4% |
| Race ratio | Black or African American, 4.1% Unknown, 4.4% Hispanic or Latino, 7.2% Asian, 25.4% White, 58.7% 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 | 11% | 9% |