6 Skills You Need to Become a Data Science Superhero

TIBCO Data Science Superheroes
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Just in the last half a decade, there has been a 344 percent increase in demand for data scientists. But since the workforce can’t automatically shift to meet this demand, there was a shortage of nearly 150,000 data scientists last year. 

Despite the fact that demand for data scientists outstrips supply, the field is still extremely competitive as data scientists clamor for the top positions. To be more valuable to companies and earn these positions, a plethora of skills are needed.

Below are the top six skills, consistent across the industry, that you need to focus on in order to develop your inner data science superhero. 

  1. Captain Obvious: Develop Python Skills. Almost every data science project could be improved with Python scripting. When looking at employing data scientists, the top desired skill is Python. While there are many open source languages available today, Python consistently takes first place across the data science industry. 
  2. Agent Collaboration: Develop People Skills. Often overlooked, people skills for data scientists are critical. With more and more citizen data scientists and business users getting involved in data science projects, having business acumen and good communication skills, playing well with others, and building trust and engagement is critical for a data scientist. 
  3. The Incredible Scaler: Develop Your Ability to Scale. Innovative companies today are racing to scale with data science, AI, and ML. But there are several barriers you must overcome first, including DevOps considerations, implementing a low-code/no-code analytics environment, balancing open source with an ability to scale, and infusing analytics into the business for real value. 
  4. Doctor Data: Develop Your Inner Data Engineer. Wonderful data scientists make raw data enterprise ready with data engineering. That means showing expertise in data prep, federation and virtualization technologies, SQL, and master data management and reference data management. 
  5. Ethos: Keep Ethics in Mind. Remember, just because you can do something does not mean you should do something. With these new data science superpowers, comes great responsibility to consider ethics, privacy, and regulatory issues in your work. 
  6. Vog: Learn to Soar in the Cloud. Fluency in the diversity of cloud computing solutions available today can bring great value to organizations today. Make sure you consider the following in any cloud computing project: ensure your cloud instance meets the business requirements you are looking to fill, think about cross-cloud compatibility, and the possibility of hybrid cloud environments. 

Do not become too comfortable being a data scientist. With the demand that we are experiencing it is an easy trap. By focusing your time and effort on a few key areas, you will develop your inner data science superhero and maintain relevance in this competitive and rewarding career. This was just an overview of the skills, make sure to watch the full webinar to gain more insight into why these areas are so valuable and details on how to up your game.