Figure 13. This plot shows an interactive boxplot of the salary distribution between job types.

Students are often interested in comparing the financial aspects of data analysis, data science, and machine learning roles. The boxplot reveals that machine learning roles have the highest median and spread of compensation, while data analysis has the lowest median. Data science falls in between, but interestingly has more outliers, likely due to the types of companies hiring. By hovering over the outliers, we can see what company names those data points refer to; they include SAIC, Reddit, and Dave Inc., which may offer higher salaries than other companies because SAIC and Reddit are large companies in their respective industries, while Dave Inc. is a financial technology firm that most likely values its data analyst hires.

Figure 14. This plot shows an interactive boxplot of the salary distribution between job types.

DSAN Students may also be curious to see how compensation differs across these three job types between the DC area and the rest of the United States. The boxplots reveals that the median for machine learning salaries are much higher in DC compared to the rest of the US. DC Machine learning salaries are also still higher than those of data analysis and data science roles. However, the 1st and 2nd quartiles for data analysis compensation in DC are much lower than the US. This may be due to the high concentration of non-profits and government agencies in the DC area as these organizations are more likely looking to hire data analysts as opposed to machine learning engineers and may have different budget constraints compared to private companies in other parts of the country.