As one of the most exciting fields in the recent years, many people are looking for the right path to break into data science and machine learning. Using a data-driven approach, I decided to dig deeper to uncover the answers to the most common questions. I analyzed data obtained from Glassdoor to answer the following 3 questions:
- What are the top industries hiring data professionals
To answer my question, I grouped the data by sector and visualized the top 10 sectors that has posted jobs for data professionals.
The result matched my expectations, where the information technology sector is the one most in demand for data professionals.
2. What tools are the most important to learn
Another question in which there is a lot of debate around is which tools should you learn to land a data job. Many people are learning tens of new tools and technologies to keep up with the rapid advancement in this field.
I decided to classify the job posting for senior positions by adding a new feature. Afterwards I created a pie chart to see which technology is most in demand for senior positions only.
The chart above shows us that knowledge of Python programming language is the most in demand skill for senior job positions. The second top skill is Excel, which many people nowadays underestimate as a powerful tool to analyze data.
3. Which data role has the highest salary
Finally, I wondered which job title in the field of data science had the highest salary. In order to take a closer look at this, I classified the job postings into a uniform job title naming convention, and I represented my findings in a bar chart.
Here, we can see that Machine Learning Engineers, Data Architects and Data Scientists are the highest paid data professionals in the market.