Top 2 Data Scientist Skills You Need in 2021

Top 2 Data Scientist Skills You Need in 2021

Leveraging the use of Big Data as an insight-generating engine has driven the demand for data scientists at the enterprise-level across all industry verticals. Whether it is to refine the process of product development, improve customer retention, or mine through data to find new business opportunities, organizations are increasingly relying on the data scientist skills to sustain, grow, and stay one step ahead of the competition.

Skills Required to Become a Data Scientist

If you are an aspiring data scientist, the information in this article can help guide you on your path toward a lucrative career in this exciting and growing industry. 

If you are a data analytics director at an organization, you can leverage the information to train your existing team of data scientists with the top data science skills, which can make them more productive and efficient with their work.

Technical Skills Required to Become a Data Scientist

One of the most important technical data scientist skills is statistical analysis and computing, mining, and processing large data sets. This also includes extracting the data that is considered valuable. 

 

Some data scientists have a Ph.D. or Master’s degree in statistics, computer science, or engineering. This educational background provides a strong foundation for any aspiring data scientist, and also teaches the essential data scientist skills and Big Data skills needed to succeed in the field, including mathematics, programming, and statistics. 

 

There are some schools that now offer specialized programs tailored to the educational requirements for pursuing a career in data science, giving students the option to focus on the field of study they are most interested in, and in a shorter period of time. 

 

Some of the many options available include Massive Open Online Courses (MOOCs) or bootcamps, such as Simplilearn’s Big Data & Analytics certification courses. These types of programs offer practical learning methods that you will not find in the confines of the textbook, including a hands-on approach to learning in-demand data science skills, Capstone projects, and other exercises that help prepare students to become data scientists.

 

Other technical skills required to become a data scientist include:

 

Programming

You need to have knowledge of various programming languages, such as Python, Perl, C/C++, SQL, and Java, with Python being the most common coding language required in data science roles. These programming languages help data scientists organize unstructured data sets.

Knowledge of SAS and Other Analytical Tools

An understanding of analytical tools is a helpful data scientist skill for extracting valuable information from an organized data set. SAS, Hadoop, Spark, Hive, Pig, and R are the most popular data analytical tools that data scientists use. Certifications can help you establish your expertise in these analytical tools and help you gain this valuable data scientist skill!

Adept at Working with Unstructured Data

Data scientists should have experience working with unstructured data that comes from different channels and sources. For example, if a data scientist is working on a project to help the marketing team provide insightful research, the professional should be well adept at handling social media as well

 


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