In 2020, data has become a new useful resource and data science has become the most popular career growth opportunity. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from large datasets. Data science is related to data mining, deep learning, and big data.
Data science is a quantitative approach that determines qualitative aspects based on calculations and predictions. Thus, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic design, and business. In 2015, the American Statistical Association identified database management, statistics, and machine learning, and distributed and parallel systems as the three emerging foundational professional domains.
Applications of Data Science
Big data is very quickly becoming a vital tool for businesses and companies of all sizes. The availability and interpretation of big data have altered the business models of old industries and enabled the creation of new ones. Data-driven businesses are worth $1.2 trillion collectively in 2020, an increase from $333 billion in the year 2015. Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations.
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One of the best benefits of data science is the ability for sales and marketing teams to understand their audience and with this knowledge; an organization can create the best possible customer experiences. One of the advantages of data science is that organizations can find when and where their products sell best. This can help deliver the right products at the right time and can help companies develop new products to meet their customers’ needs.
Career Choice as Data Science
Data science is a growing field. A career as a data scientist is ranked as the third-best job in America for 2020 by Glassdoor and was ranked as number one job from 2016-2019. Data scientists have a median salary of $118,370 per year or $56.91 per hour. Job growth in this field is also above average, with a projected increase of 16% from 2018 to 2028. The largest employer of data scientists in the US is the federal government, employing 28% of the data science workforce. Other large employers of data scientists are computer system design services, research and development laboratories, and colleges and universities. Typically, data scientists work full time, and some work more than 40 hours a week.
In order to become a data scientist, there is a significant amount of education and experience required. The first step in becoming a data scientist is to earn a bachelor's degree, typically in a field related to computing or mathematics. Most data scientists also complete a master’s degree or a Ph.D. in data science. Some jobs corresponding to data science include Data Scientists, Machine learning scientists, Data analysts, Data consultants, Data architects, and Application architects.
“A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.”-DJ Patil (Chief Data Scientist)
What Data Scientist does
A data scientist examines and explores the organization’s data, after which they recommend and prescribe certain actions that will help improve the institution’s performance, better customer engagement, and ultimately increase profitability. During their interaction with the organization’s current analytics system data scientists question the existing processes and assumptions for the purpose of developing additional methods and analytical algorithms as per the requirement.
An experienced data scientist is likely to be a trusted advisor and strategic partner to the organization’s top management by ensuring that the staff maximizes their analytic skills. A data scientist communicates and demonstrates the value of the institution’s data to facilitate improved decision-making processes across the entire organization, through measuring, tracking, and recording performance metrics and other information.
With the advent of data scientists, data gathering and analyzing from various channels has minimized high stake risks. Data scientists create models using existing data that simulate a variety of probable action plans by which an organization can get the best business outcomes. They hire someone who can measure the key metrics that are related to important changes and quantify those parameters for organizational success. From Google Analytics to customer surveys, most companies have at least one source of customer data collection. IBM predicts that demand for data scientists will rise by 28% as it is a rapidly growing realm.
“Just like there was California Gold Rush in the early 1900s, there’s Data Science Gold Rush now and you need to be leading this Goldrush.”- Manvendra Singh(Chief Data Science Mentor, INSAID)
Summary
The importance of data science is based on the ability to take existing data that is not necessarily useful on its own and combine it with other data points to generate insights an organization can use to learn more about its customers and audience. With this in-depth knowledge, organizations can customize services and products to satisfy customer needs, and make the organization flourish by increasing their profit margins. With the amount of information available on talent through social media, corporate databases, and job search portals data science specialists can work their way through all these data points to find the candidates who are the best fit for the organization’s needs.
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To sum up, Data science can maximize revenues and add value to those businesses which can utilize their data optimally. It acts as a valuable asset to all those companies which invest the majority of the investment amount in data science in that industry.
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Technical Team Member