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.
Consequently, 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. In this article, we will dive into the technical and non-technical data scientist skills.
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:
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 as such, can be difficult to assess simply by looking at educational qualifications, certifications, and so on. They include:
Shashi Upadhyay, the CEO of Lattice, once referred to data scientists as “unicorns,” calling them “professionals with a diverse skillset 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. The right training and certification to acquire the right data scientist skills, however, 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.
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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