Data science, as the name implies, refers to the science of analyzing data. Its key objective is to assemble and store structured and unstructured data to obtain valuable information. Data science is a vast field, including several skills such as analytics, mathematics, and statistics. These scientists generally help in improving customer retention and product development. They further analyze the current and future marketing trends to develop fresh business opportunities for sustainable growth. 

According to the recent stats, 44 zettabytes of data were available worldwide, which is likely to reach more than 460 zettabytes by 2025. With the incredible pace of digitalization, organizations, governments, and nonprofits seek expert data scientists to handle the big data and make better decisions for them. Organizations indeed require persons with a substantial amount of expertise to extract, interpret and manage critical information from the available data.

It is worth mentioning that according to the recent insights, there will be around three million job openings for data scientists by the year 2021. However, if you’re an IT geek, then this article is for you. Below we’ve discussed all the essential points that would help you to develop a firm understanding of the profession.

1. Education Criteria

To be a data scientist, you ought to have strong background knowledge regarding the field of study. For this, it is best to secure a bachelor’s degree in any of the following education programs. These include statistics, computer science, social or physical sciences. Earning a bachelor’s degree in a relevant field will allow you to process and analyze massive data. 

Notably, most data scientists opt for additional education, preferably an onsite or online masters in data science, to augment their technical and non-technical skills. Since most students’ ultimate goal is to earn a handsome amount by implementing theoretical knowledge into the practical world, opting for an online degree is best to keep your professional career and learning parallel.

2. Technical Skills 

Like every other profession, having theoretical knowledge is not enough. IT fields such as data science require some essential technical skills to improve work efficiency. Perhaps, some of the most important technical skills include:

• Python: Python is used commonly in all stages of data science procedures among several programming languages. It can hold numerous data formats, which allows you to code SQL tables efficiently. You can generate datasets with python coding and get them on google effortlessly.
• Structured query language (SQL): SQL coding is a programming language that helps add, remove, and even obtain essential data from any database. It is undoubtedly a significant component in the data science process. It allows programmers to write complex queries using SQL coding. However, SQL coding is not limited to these only. It can also be used in analytical functions and altering databases’ structures.
• R programming language: While learning analytical tools, programmers should consider R as a crucial programming language. When you encounter any statistical or analytical issue, implementing R programming knowledge aids in solving the problems. 

3. Non-Technical Skills

Just like technical skills, non-technical skills have a distinct position in the profession. As a data scientist, having non-technical skills would help you to complete the work processes smoothly. Your attitude has an immense impact on the organization and is independent of your educational background and experience.

• Powerful business acuity: A robust business understanding is necessary for any organization to flourish and meet new business prospects. As a data scientist, you have a massive responsibility to face potential challenges that comes your way. Keen insights related to the industry and the potential problems hindering the process would benefit the organization to grow better. Besides, your employers will expect you to know about the business issues and provide them with the solution that can benefit the company. 
• Excellent communication skills: Like every other profession, strong communication skills are necessary to execute the task successfully. A data scientist with strong communication skills makes other team members understand your work. It further helps in leveraging the tasks more effortlessly. In this manner, your organization will get benefits from your services.
• Teamwork in the organization: As a data scientist, you cannot work solely and might require working with a team of executives. Also, your job role may include performing and coordinating with product managers, marketers, etc., to execute the business plans successfully. 

Perhaps, your job will require you to think like a strategist to deliver services that generate maximum profits. Hence strong teamwork is thus necessary to execute your tasks effectively.

Wrap Up

Data science is a gigantic field with multiple opportunities for a productive career. It helps businesses in developing data-driven instructions to introduce further developments. Organizations of the present-day seek highly skilled data scientists with technical and soft skills for a successful future. Since almost every industry is now accepting data-driven information, there seems a great scope of these professionals worldwide.