Figure 4. This plot shows an interactive treemap of top 30 words describing data analysis qualifications.

Let's explore the qualifications required for a data analyst role. The treemap reveals key words such as "experience", "year", "data", "communication", "management", "statistics", "SQL", and "Excel". These words suggest that a data analyst role requires a few years of experience working with data, effective communication skills to work with teams and clients, and some management experience. Moreover, hard skills such as statistics, SQL, and Excel are crucial to have a background in if applying to data analysis roles.

Figure 5. This plot shows an interactive treemap of top 30 words describing data science qualifications.

Words such as "statistics", "machine learning", and "mathematics" underscore the importance of having strong quantitative skills. Additionally, proficiency in tools such as "Python" and "R" are considered essential for most data science positions; this is expected as we saw that responsibilities include the development of predictive algorithms and models. The word, "sql" is also seen here which is not surprising as some companies, such as Veeva Systems, require data scientists to use query search engines in which knowdlege of sql is important.

Figure 6. This plot shows an interactive treemap of top 30 words describing machine learning qualifications.

The treemap displays qualifications necessary for a machine learning role, with some unique words that stand out such as "learning," "engineering," "deep," and "software." These suggest that familiarity with software engineering and deep learning is required. Additionally, "pytorch" and "tensorflow" are highlighted as essential python libraries for developing advanced machine learning models, so knowledge and experience with these are crucial for machine learning roles.