Examining 1,170 data scientist job advertisements
The year is 2020, and the data science job market continues to evolve - and so are companies looking for data scientists to join their teams.
The 365 Data Science team conducted a study based on 1,170 data scientist job postings in the United States. The research aims to uncover the typical data scientist profile desired by hiring firms, along with the soft and technical skills applicants needs for landing data scientist jobs.
The research analyzed 1,170 data science job openings from 357 unique companies. This gives us higher confidence that the reported findings are not biased towards the needs of a few companies.
Out of the 1,170 job openings, 823 of them came from firms that didn’t have a profile on the job gate website (they posted through agencies). That’s why we don’t have company size data for these organizations.
Nevertheless, the distribution of the companies for which we have data is heavily skewed towards big firms with over 10,000 employees. This suggests that large corporations are the ones hiring most data scientists today.
With reference to location, we determined that companies from 38 U.S. states were actively looking for data scientists to join their team at the time of data collection. The top 12 among them are: California, Virginia, Washington, New York, Massachusetts, Maryland, Texas, Colorado, Michigan, Ohio, New Jersey, and Florida.
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Credentials appear to be of utmost importance for employers. 544 of them asked for a bachelor’s degree or higher; another 367 wanted a master’s degree, 50 companies looked for Ph.D. graduates, while 209 job openings listed no educational requirements.
For those who find company size as imperative as the job itself, it may be useful to consider the link between the educational level required and the size of enterprise. We found out that small organizations (1-100 employees) are mostly interested in hiring master’s degree holders rather than Ph.D. graduates. For big firms, however, both bachelor’s and master’s were, more or less, equally desirable.
In terms of fields of study that employers prefer, data science, statistics, mathematics, computer science, and engineering are among the most sought-after disciplines. By contrast, information technology (IT), economics, and physics are far less popular in that regard. Bear in mind that we collected the data by extracting only the first three fields listed in the job descriptions. There may be other knowledge domains that companies consider compatible with the tasks and responsibilities of a data scientist as well.
Оn average, companies require a minimum of 4.2 years of experience as a data scientist, and 5.2 years working in a related field that we refer to as “general work experience.”
Again, company size affects the job requirements concerning expected years of experience. Knowing that small companies operate with a limited number of people, it seems reasonable for these organizations to look for experienced candidates who don’t need to spend time attending an induction training. At the same time, sizeable enterprises, with the myriad of resources available to them, appear to favor training someone in-house. Thus, they are more likely to extend a job offer to a less experienced candidate.
Overall, employers require similar work experience for all applicants, regardless of the academic degree a candidate holds.
To be hired as a data scientist, you’ll need to be skilled in at least one programming language. Our research shows that proficiency in Python is the primary computer-language competency organizations expect from an applicant. Unsurprisingly, next in line are R and SQL, followed by Scala, Java, and C++.
Besides Python programming, employers look for people with solid technical skills, such as machine learning (ML) and statistics. As for machine learning, deep learning is ranked as the top ML technique, along with clustering and natural language processing (NLP).
The research also considered the significance of database/cloud skills and data visualization skills. It seems that Spark, AWS, and Hadoop are some of the most in-demand database competencies for a data scientist. With respect to data visualization, there are two main tools mentioned in the job ads: Tableau (228 mentions) and Power BI (79 mentions).
How about the range of soft skills that employers require?
Our keyword analysis identified that communication skills and teamwork were among the few highlighted competencies that employers cited. Out of 1,170 job posts, 368 of them put a significant emphasis on communication. Therefore, one should not exclude communication skills from their personal development plan. It would certainly be an added advantage to convey good communication and interpersonal skills during your data science interviews!
We appreciate you taking the time to read the study our team conducted on a sample of 1,170 data scientist job openings located in the USA in 2020! Hopefully, this information will prove to be useful for people who want to pursue a career in data science.