When Does Education Level Matter in Data Science?

When Does Education Level Matter in Data Science?

Data scientists are highly educated. In our study of data scientists, we found that over half of them, both men and women, hold either a Masters or PhD degree and about a quarter of them hold a 4-year degree. The level of educational attainment is related to proficiency in data science skills (more advanced degrees are associated with greater proficiency), but only for specific types of data scientists.

Data scientists have the hottest jobs in America this year. Due to a shortage of these data-savvy people, data scientists are in high demand and well-paid. Because of this demand, many universities are now offering graduate degrees in the field of big data and data science (see here for a recent ranking of the top 50 Big Data graduate programs). But how much education does a person need to help their company successfully solve problems using data. Working data professionals offer their answers to this question (see this thread on Quora). We sought to take a more rigorous approach to answer this question. In ourongoing study of data scientists, we examined if data professional's education level was related to their proficiency across different data science skills.

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In our study, we asked data professionals to rate their proficiency levels of 25 specific data science skills across five broad skill areas: Business, Technology, Programming, Math & Modeling and Statistics. We also asked these professionals to indicate their job role: Business Management, Developer, Creative and Researcher. Finally, we asked about their level of education: high school / tech / 2-year degree, 4-year degree, Masters degree and PhD degree. The results appear below.

We looked at educational attainment by job role. The results are presented in Figure 1. On the whole, these data science professionals in this sample are highly educated. Irrespective of their job role, most of these professionals held, at least, a 4-year college degree (87% to 97%).

Data professionals who self-identified as Business Management or Creatives held the most Masters degree (58% hold this degree).

Most of the data professionals who self-identified as Developers held either a 4-year degree (43%) and a Masters degree (52%). None of them held a PhD.

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Data professionals who self-identify as Researchers possessed the largest number of PhD degrees (41% of them held this degree) compared to data professionals in other data science roles. Researchers held the most advanced degrees (80% held either a PhD or Masters degree).

For our study, skill proficiency could vary from 0 (none) to 100 (expert). A skill proficiency rating of 60 indicated that the data professional could essentially perform the skill independently, without help from others (see dotted line in Figure 2). See this blog post for a more complete discussion of the rating scale.

Data professionals with a PhD degree possessed proficiency (proficiency rating greater than 60) to independently perform more skills (10 skills) compared to the data professionals with other degrees (Masters degree: 5 skills; 4-year degree: 2 skills; High school degree: 1 skill).

While a PhD degree can be granted in a variety of disciplines, a common theme among them is that they are research-intensive; as part of your PhD, you learn how to conduct research, typically culminating in an independent research project focused on the PhD candidate's area of interest. Not surprisingly, we found that data professionals with a PhD were generally more proficient in skills related to math and statistics, skills necessary to conduct scientific research.;

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