As the demand for data scientists increases, the discipline presents an enticing career path for students and existing professionals. This includes those who are not data scientists but are obsessed with data and data science, which has left them asking about what data science skills and big data skills are needed to pursue careers in data science.  

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 data scientist skills to sustain, grow, and stay one step ahead of the competition. Also, in this article, we will dive into technical and non-technical skills required for data scientists.

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Skills Required For Data Scientists

The 2 types of important skills are:

  1. Technical
  2. Non-technical skills
  • 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.

Moving forward, let us discuss what are the technical skills required for a data scientist role.

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Technical Skills Required For Data Scientists

Some of the most important technical data scientist skills are:

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:

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 data scientist skills required include:

Skill #1- 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.

# Pro tip: To learn more about the Programming languages, click here!

Skill #2- Knowledge of SAS and Other Analytical Tools

Understanding analytical tools is one of the most helpful data scientist skills 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 science skill!

Skill #3- 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.

Some of the other data scientist skills required are Machine Learning, Artificial intelligence, Deep learning, Probability and Statistics.

Moving forward, let's discuss the non-technical skills.

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Non-Technical Skills Required For Data Scientists

Along with the technical data scientist skills, we will now shift our focus on non-technical skills that are required to become a data scientist. These refer to personal skills and can be difficult to assess simply by looking at educational qualifications, certifications, and so on. They include:

Skill #1- A Strong Business Acumen

The best way to productively channel technical skills is to have strong business acumen. Without it, an aspiring data scientist may not be able to discern the problems and potential challenges that need to be solved in order for an organization to grow. This is essential for helping the organization you’re working for explore new business opportunities.

Skill #2 - Strong Communication Skills

Next on the list of top data scientist skills is communication. Data scientists clearly understand how to extract, understand, and analyze data. However, for you to be successful in your role, and for your organization to benefit from your services, you should be able to successfully communicate your findings with team members who don’t have the same professional background as you.  

#pro tip, have a look at these resources:

    1. Roles of communication in projects
    2. Effective communication
    3. Importance of good communication

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Skill #3 - Great Data Intuition

This is perhaps one of the most significant non-technical data scientist skills. Valuable data insights are not always apparent in large data sets, and a knowledgeable data scientist has intuition and knows when to look beyond the surface for insightful information. This makes data scientists more efficient in their work, and gaining this skill comes from experience and the right training. However, this data scientist skill comes with experience and bootcamps are a great way of polishing it.  

These were some of the data scientist skills and qualifications required to grow in this field.

Data Scientists – The Unicorns

Shashi Upadhyay, the CEO of Lattice, once referred to data scientists as “unicorns,” calling them “professionals with a diverse skill set that is not commonly found in a single individual.” This explains why data scientists are so valued, and why becoming one can potentially be challenging. However, the right training and certification to acquire the right data scientist skills are often the building blocks for success. Take the first step toward reaching your career goals and enroll in an accredited Data Science program today.

About the Author

Ronald Van LoonRonald Van Loon

Named by Onalytica as the world's #1 influencer in Data and Analytics, Automation, and the Future Economy (Tech), Ronald is the CEO of Intelligent World and one of the top thought leaders in Data Science and Digital Transformation.

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  • *According to Simplilearn survey conducted and subject to terms & conditions with Ernst & Young LLP (EY) as Process Advisors