For years, the profession of data scientist has been named as the number one job in the United States. The demand for professionals in the field of data science is very high, whereas the supply is low.
Regardless, the U.S. Bureau of Labor Statistics has reported that we should expect a further 27.9 percent increase in demand for data science skills in the workplace in the next decade. They have also stated that the number of data scientist jobs is expected to grow 19 percent over the next two decades, which is almost three times faster than the average growth rate for other jobs.
Despite its popularity, many individuals, especially those working outside data-related fields, struggle to understand the profession and role of a data scientist. What does a data scientist do? What is data science used for? How does it help organizations and corporations? Read on to find the answers to these questions and more. Who knows, maybe this is the article that introduces you to your dream job.
What Is Data Science Used For?
Nowadays, data science has become a sort of fuel for the business industry. Because of the enormous amounts of data that are produced daily by individuals and companies, industries are beginning to take advantage of this flowing information through data science.
Data science is used for various purposes, depending on the industry. To illustrate, the medical industry uses data science for image analysis, to provide virtual assistance for patients, create algorithms to detect potential diseases, among other uses.
On the other hand, the marketing industry uses data science for targeting ads, recommendation engines, to get more details about customers, run real-time a/b testing, improve customer experience, and so on.
Data science is also used by the media and entertainment industry, the airline industry, banking, financial services, and insurance industry, retail, telecommunication, and many others.
What Is a Data Scientist?
A data scientist is a professional in the field of data science. They are responsible for gathering, analyzing, and interpreting sets of data related to the company they work for. This profession combines various fields, such as computer science, statistics, and mathematics in order to extract the necessary insights from datasets.
The profession of a data scientist has only just become more popular. About a decade ago, not many companies used big data or cared about the benefits of having a data scientist on their team. Nevertheless, data keeps being created and businesses can no longer ignore the valuable information and insight data scientists can provide. Nowadays, some of the biggest companies, like Netflix, Google, Coca Cola, are all data-driven and include many data scientists in their crew.
More than 79% of data scientists have earned a bachelor’s degree in data science or a closely related field such as computer science, computer engineering, information technology, math, and statistics, or any other related field. They generally start their careers as data analysts, or junior data scientists and work their way up.
To fully answer the question of what a data scientist is, we must also understand what they do.
What does a data scientist do?
The simplest answer to this question would be that data scientists gather data, analyze it, and use the information to help understand and improve the company’s business processes by assisting in problem-solving and decision-making. They design data modeling processes, algorithms, and predictive models to extract information from the gathered data. Then after analyzing that data, they use the insight from results to help solve problems or help with decision making.
Although each data science project is unique, and the data scientists have different responsibilities during each one, on a normal workday they will be dealing with one of the below-mentioned duties.
You can’t be a data scientist if there is no data to work with, that is why data collection is an essential part of any data science project. There are various helpful tools that can be used to accumulate the necessary data. There are the classic ETL or ELT tools like Oracle Data Integrator, Microsoft DTS, and IBM DataStage, as well as some Cloud integration tools like Azure Data Factory, and Talend.
After gathering the data, data scientists proceed to transform it. This transformation is done by altering the structure and format of the raw data, in order for the system to be able to work properly during the analysis process.
With the data in hand, data scientists use data-driven techniques to solve business-related problems. An example of such a problem would be a supply chain efficiency issue. As a solution, data scientists create data models that provide insight into what affects the speed at which products move through the supply chain.
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Working with programming languages
Some of the most notable programming languages that data scientists use are Python, R, C/C++, SAS, Scala, and SQL among others.
Searching for patterns
Data scientists use special algorithms to distinguish and classify data according to a set of criteria. This way they can recognize patterns as well as spot trends that can help the company.
Communicating with others
Data scientists work closely with various other data-related professionals, as well as stakeholders in order to understand their requests and the company’s goals so then they can use data to easily achieve them. Most projects require data scientists to collaborate with other IT professionals to create algorithms, data models, come up with new data-driven techniques, etc.
Kick-Start Your Data Scientist Career
If you are interested in becoming a data scientist, it is important to prepare yourself for what is a very challenging but rewarding profession. You can kick-start your journey by pursuing a degree program in this field. An excellent option would be Bay Atlantic University, one of the universities that offer a bachelor’s degree program in data science. This program is designed to integrate various scientific methods from statistics, computer science, and data-based business management to further develop the students’ knowledge and skills necessary for a successful career in data science. With this program, you will be qualified for more than just a job as a data scientist, but for jobs as a data analyst, data science/analytics manager, database administrator, big data engineer, data mining engineer, machine learning engineer, data architect, and many other positions as well.
Data science is one of the most in-demand jobs. Because of this demand, combined with the shortage of skilled professionals in the field, a data science career is not only exciting but also highly rewarding. Join our program and take the first step towards success in your data science journey.