Due to the use of Big Data as an insight-generating engine across all vertical sectors, data scientists are in high demand at the enterprise level. Whether it's to improve customer retention, optimize that product development process, or even mine data to identify new business opportunities, corporations actively depend on data scientists' ability to sustain, expand, and even stay one step ahead of their competition. 

In this article, we will look at the practical technical and non-technical skills required for becoming a data scientist.

Technical Skills for Data Scientists 

Skill #1 Programming

Python is the most often used coding language in data science professions, but you also need to be proficient in other programming languages, including HTML, C/C++, SQL, and Java. These programming languages aid in organizing unstructured data sets for data scientists.

Skill #2 Understanding SAS and other Analytical Tools

One of the most useful data scientist skills for obtaining meaningful information from a structured data set is understanding analytical tools. Data scientists frequently utilize SAS, MySQL, Spark, Swarm, Pig, and R as data analysis tools. You can demonstrate your proficiency with many of these analytical tools and develop these vital data science skills by earning IBM certification from a data science course in Mumbai. 

Skill #3 Adept at Working With Unstructured Data

Data scientists need to have prior expertise working to handle unstructured data from many sources and channels. For instance, a data scientist should be skilled in managing social media if they are working on a project to assist the marketing team in providing insightful research.

Deep learning, artificial intelligence, machine learning techniques, probability, and statistics are some more skills needed by data scientists.

Non-Technical Skills for data scientists

We will now change our focus to the non-technical abilities needed to want to be a data scientist in addition to the technical skills. These personal abilities can be challenging to evaluate solely by looking at educational background, credentials, etc. They consist of the following:

Skill #1 Business Acumen

The best use of technical expertise is when it is matched with wise business decisions. A nascent data scientist could recognize the problems and challenges to be faced by a business to develop without it. This is essential for helping the company you work for pursuing new business opportunities.

Skill #2 Strong Communication Skills

Communication is next on this list of the foremost data scientist abilities. Data analysts are skilled at gathering, understanding, and analyzing data. However, if you want to be successful in your role and support your organization, you must be able to clearly communicate your results with other team members that have diverse professional backgrounds.

Get Started Today

Data Science is a challenging field but not impossible if you put in the efforts. There are many online certifications and training offered to assist you in advancing your skills. The IBM-accredited data science certification course in Mumbai is one such program that provides real-world learning strategies you won't find in a textbook, like hands-on learning of in-demand data science skills, Capstone projects, and other activities that help students get ready to become data scientists.