Data science as the most prospective career of the 21st century

Introduction 

As per a report by Gartner, the amount of data that would be generated in the year 2025 would be 50 times more than that generated in 2020. To deal with such a humongous amount of data is a grand challenge in itself. The businesses that would be able to brave this challenge would be able to stand out in this data race. Others may be gently wiped out. This trivial observation is enough to signify the impact that data science would have on businesses in the coming times. 

Diversity in data science 

Data science is largely dependent on mining large sets of data and deriving critical insights from it. However, the scope of data science cannot be limited to the above definition. The most important trend that reveals the diversity of data science includes customer behavior-related transactions that can be used for customer personalization in the long run. That said, data science includes under its umbrella a large set of tools, techniques, and even other fields of data related to technology. The methodologies of data science can be leveraged not only for improving customer experience but also for showing more personalized recommendations.

The diversity of data science can be attributed to the fact that it incorporates the fields of machine learning, artificial intelligence, business intelligence, and the like in its domain. Data science enables us to identify various flaws in data that hinder the growth of a prospective company. By collecting and cleansing huge sets of unstructured data, we can construct statistical models that help in knowledge discovery and data visualization.

Data scientist salary

There is no doubt in the fact that data science is one of the highest-paid professions in the world. If we look at the entry-level jobs in data science, we find the pay scale to range from 12 lakh to 24 lakh per annum. After a data scientist has gained experience of more than 5 years, he is expected to gain a salary package of about 35 lakh per annum. Some of the most senior data scientists who have experience of more than 10 years in the field earn about 150 million in a year. The above figures vary according to the nature of various companies and also the job requirements. The geo-political location also has a key impact on the pay scales of a data scientist. As per a report by payscale.com, the approximate pay scale for a data scientist working in impetus is around 19 million per year. It is about 10 million for data scientists working with McKinsey. For Wipro technologies and American Express, it is about 12 million. IBM Corporation offers a package of more than 15 million per year.

How to become a data scientist?

To become a data scientist, one should be aware of the entire data lifecycle that includes data analysis and processing. A data scientist should be able to extract, process, and validate large data sets. Some of the initial steps that a person can take to find a prospective career in data science include the acquisition of knowledge about machine learning, advanced algorithms, operation research, statistics, mathematical models, and data structures. Additionally, one can acquire knowledge of important tools like Spark and Hadoop and specialize in data visualization. As data science is a very versatile and interdisciplinary academic field, the person must be ready to acquire knowledge from various sources. A person who acquires knowledge of fields like computer science, finance, economics, business management, and mathematics is ready to usher into this discipline. 

Research prospects

As a data scientist, you will be able to work closely with data and provide solutions for decision sciences. The design and development of various algorithms for managing huge data sets are also one of the major research prospects when it comes to data science. Other prospective research domains include statistical modeling and distributed computing. The research horizons of a data scientist are broadened when he is equipped with the knowledge of programming languages like R, SAS, Python, and SQL. Moreover, specialization in Big Data Analytics helps in the design, development, and maintenance of large databases which opens a new door of research for data architects.

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Concluding remarks 

Data science is one of the most prominent and progressive careers that a technical professional can aspire for. All that is needed apart from skill acquisition is a zeal to master multidisciplinary fields and step into the environs of inquisitive research.