Top 10 Skills For A Successful Data Scientist

Rapid technological advancements, accelerating the importance and use of data, and increasing data literacy have changed data science’s meaning. Before data science was synonymous with data collection and analysis but today, it is a multidisciplinary field that uses scientific, statistical, and mathematical processes, formulas, and algorithms to make sense of data generated by various enterprises.

Data scientists are evolving with the changing times. Honing skills, staying updated with the latest trends, learning new skills, and studying case studies are some of how data scientists embrace change in the field. This article will discuss the secret skills required by a data scientist.



How To Become A Data Scientist?

The dictionary defines prerequisites as something necessary to carry out a function. Therefore, to successfully complete assigned tasks, a data scientist must adhere to some prerequisites. In this part of the article, we will look at the prerequisite required to become a data scientist; check out:

  • Who is a data scientist?
  • Top skills required for data scientist
  • Popular data science jobs
  • How to make a career in data science?

In the succeeding part of the article, we will discuss the above-mentioned in detail.

 

Who Is A Data Scientist?

Data scientists are trained and skilled individuals who perform data wrangling, data segregation, collection, and analysis, among other data science-related functions. Their prolific knowledge of mathematical formulas and statistical techniques is peculiar and unique.
Sometimes data scientists are referred to as analytical experts who utilize their skills to gain meaningful insights for the organization to survive in complex market conditions or attain success and growth.

Top Skills Required For Data Scientist

Here are the top skills required for a data scientist to perform their task efficiently.

  1. Probability and statistics

Organizations often apply data-driven approaches, from predictive analysis to AI-driven applications, into their process. A data scientist well-versed with probability and statics can aid the process by providing expert knowledge and skill. In addition, many aspiring data scientists take specialized certificate courses to brush on their analytic skills.

  1. Programming languages and software
    Companies are integrating various Artificial intelligence and machine learning-driven applications into businesses to attain automation and efficiency. However, the operation and integration of these systems are the responsibility of data scientists. Therefore, an aspiring data scientist should know about different programming languages and data science software.
  2. Data wrangling
    Data scientists often deal with unstructured and raw data. Thus, being well-versed in the data wrangling process is imperative to attain efficiency and timeliness. Experts define data wrangling as cleaning and organizing raw data into a desired format or structure that helps data scientists analyze it faster and easier. Data wrangling is an important process that every enterprise undertakes. Therefore, it has more importance than other data science processes.
  3. Database management
    A database is an application where the filtered data is presented in the form of a table, schema or other entities. Most data scientists work constitutes with database management, and basic knowledge helps them perform their duties efficiently and in less time. In addition, many certification courses help aspiring data scientists learn the basics of database management.
  4. Data visualization
    Experts define data visualization as visualizing collected and analyzed data in the form of a graph, table, or pie chart. A data scientist should have a penchant for visualization to excel because they will be presenting data charts to stakeholders and managers.
  5. Machine learning and deep learning
    Machine learning and deep learning are subsets of data science. They are modern technological applications that automate business processes and prove that computer systems can be a great proxy for the human mind. Many companies have integrated different machine learning and deep learning application into their business processes. So, data scientists seeking job opportunities in the current business milieu should be akin to different machine learning and deep learning applications.
  6. Cloud computing
    Cloud computing is summarized as the process of using information technology(IT) infrastructures like applications, servers, data storage systems, and development tools to introduce automation, timeliness, and efficiency in the communication and organization of data and information.

Many companies have started using the cloud for conducting various business activities. Therefore, being well-versed with cloud computing will help data scientists to communicate effectively.

Popular Data Science Jobs

Companies are sitting over a mine of data, for which they need individuals with data science skills. Here are some popular data science jobs in demand in the current business milieu.

  • Data Engineer
  • Data analyst
  • Data Architect
  • Machine learning engineer
  • Statistician

Now that you are aware of the skills required to become a data scientist, below is how to make a career in data science.

  1. Communication skills

Data scientists convert large data sets into easy-to-understand information that can be used to make critical business decisions. Therefore, data scientists must know how to simplify complex ideas and data findings and convey the same to different departments.

However, if you lack communication skills, it might get difficult for you to translate technical jargons into plain and understandable language.

  1. Structured Thinking

Structured thinking is a framework for solving unstructured problems in the field of data science. It uses a structured approach to identify parts of the problems that might need more attention and solve problems faster.

Data scientists must have structured thinking because it helps them analyse a data set or business problem from different perspectives and understand its effect on the company and key stakeholders.

Structured thinking can be a natural skill or can even be learned.

  1. Business Acumen

Companies mostly use data science to improve their business and decision-making capabilities. Data science is also used to get accurate insights into different processes and functions of a business, spot problems, make predictions, and suggest ways to improve.

Therefore, data scientists need business acumen to make a difference in the company. Having business acumen will help them gain a better understanding about the business and make better data and predictive models to increase efficiency.

How To Make A Career In Data Science?

Companies are looking for data science professionals skilled with peculiar soft and technical skills. Therefore, to learn about the basics of data science, aspirants take up different bachelor’s or master’s degrees in data science or similar field. Some also go ahead to learn data science by pursuing certification courses.

Emeritus India has some of the best certification courses in association with renowned Indian and international educational institutes. The Indian Institute of Management, Indian Institute of Technology, and Indian School of Business are some institutes with whom we have partnered to offer some of the best data science certification, diplomas, and post-graduation courses for working professionals. So, enrol yourself in our courses to accentuate your career to new heights.

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