The Challenges of Being a Data Scientist

According to a Stack Overflow survey, 13.2% of the data scientists are looking for a new job, as they are not satisfied in their current role. So why is this happening? What are the challenges Data Scientists are facing?

Organisations around the world are looking for new ways to organise, process, and unlock their data’s full potential and translate it into high-value business insight. So we can say data is the new oil.

Seagate estimated that by 2025, the amount of data generated is to reach 163 zettabytes; ten times the amount of data produces in 2017. So you can imagine the demand for Data Scientists going through the roof. In 2012, LinkedIn released that there was a 650% growth in Data Scientists. The career is in the top-ranked best jobs listing and highest-paying jobs. 

Every sector can benefit from Data Science, so there is no reason why organisations will miss out on this opportunity. Harvard Business Review has labeled data science as the “sexiest” career of the 21st century.

Despite it being the “sexiest” career of the 21st century, every career comes with its challenges. You would imagine a job that is in such high demand, there will be fewer challenges and problems as they are critical within organisations. However, according to Financial Times, many companies seem to be failing to create jobs that benefit the drastic spark in data experts. Many of the data experts are struggling to move up the ladder or meet their career aspirations. According to a Stack Overflow survey, 13.2% of the data scientists are looking for a new job, as they are not satisfied in their current role. 

So why is this happening? What are the challenges Data Scientists are facing?

  It’s rare that data ever comes perfect or clean, causing Data Scientists to spend nearly 80% of their time cleaning and preparing data, according to Forbes. The title of this article is called ‘Most Time-Consuming, Least Enjoyable Data Science Task‘, so you can imagine why 13.2% of Data Scientists are looking for new jobs. If most of your time is spent improving the quality of data, making it accurate and consistent before doing any analysis on it; it can become very draining, mundane, and very time-consuming. 

A way to reduce the amount of time spent on preparing data and the lack of motivation of your Data Scientists, adopting emerging AI-enabled data science technologies such as Augmented Analytics. Augmented Analytics automates manual data cleansing and preparation tasks, allowing data scientists to be more productive and spend time with other tasks such as analysis that they prefer to do and enjoy. 

Cyberattacks have become more prominent since organisations have transitioned into using cloud data management. This could be a very big problem with organisations that deal with government data, and public information that needs to be protected.