Why Is There a Shortage of Data Scientists?
Data science is driving the industry crazy. It is trending everywhere. Everyone is talking about data science. Whether it’s data science in the industry or data science as a career. Over time, it has become like a superhero! Along with this, we all have frequently heard that data science is one of the most lucrative career options. Do you ever wonder why the companies are offering such a high amount of salaries to the data scientists?
The answer to this question is very simple. We value those things more which are less available. The case of data scientists is also the same. The salaries of data scientists are skyrocketing because there is a shortage of data scientists in the industry. As per the McKinsey report, the United States is facing a shortage of approximately 140,000 data scientists.
Let’s understand why there is a shortage of data scientists and what do companies look for in them.
WHY IS THERE A SHORTAGE?
The major reason why there is a shortage of data scientists in the industry is lack of skills. A person is not valued by its percentages and degrees, but by his skills. Data scientists are highly skilled persons who are supposed to possess technical skills as well as non-technical skills.
But the companies are not able to find the required data science skills in the data science aspirants. That’s why there is a huge shortage of data scientists in the industry.
The other major problem that beginners are facing is that companies are demanding a master’s degree with some years of experience. This is a major issue for them. Being a beginner, they have no experience in the domain of data science and the companies are demanding experience because it’s required for the job. So, that forms a deadlock.
Let’s have a look at the skills that companies are looking for in a data science aspirant. The skills are broadly divided into two categories, i.e. technical skills and non-technical skills.
In technical skills, a data scientist must have good command over mathematics, statistics, probability, programming, tableau, and big data technologies. Here is the list of technical skills that a data scientist must have:
- Descriptive statistics
- Inferential statistics
- Linear algebra
- Discrete math
- Optimization theory
- Database query language
- Big data technologies
Along with technical skills, non-technical skills are also important for a data scientist. Here are the non-technical skills:
- Data intuition
- Data inquisitiveness
- Business expertise
- Communication skills
These are the skills which a data scientist must possess and skills are the foremost reason why there is a shortage of data scientists in the industry. Work on the above-mentioned skills to drive your career to data science!