Do you want to enrol in a data science course? Careerera.com recommends it as a lucrative, in-demand, and steadily increasing field, but as you'll see, this prediction is shared by all major sites and experts. Data scientists have ranked as the "number one job in America" in four of the last five years, according to Glassdoor, and are still in third place this year. Data science is dubbed "the sexiest job of the twenty-first century" by Harvard Business Review. Rock stars and supermodels, step aside.

First Things: What is a Data Scientist?

Before we get into why you should become a data scientist, it's important to understand what exactly this job path entails. Data scientists, who are part mathematician, part computer scientist, and part business strategist, must be experts in numerous fields at the same time. Because of this diverse skill set, data scientists must always have one foot in the information technology industry and the other firmly planted in the business world. That's one of the reasons why data scientists are in such great demand, and why becoming one is one of the best career choices you can make.

Data science is largely concerned with the discovery of deep knowledge through data exploration and inference, and a good data scientist must have both statistical and computer abilities in order to solve complicated problems. This subject focuses on applying mathematical and algorithmic tools to solve some of the most analytically challenging business problems, utilising vast amounts of raw data to uncover hidden insights.

The basis of the data science discipline is precise and often minutia-driven analysis, as well as the development of strong judgement capabilities, and it can be a quiet and solitary field at times. Data scientists, on the other hand, must have exceptional verbal, written, and visual communication skills, as they will be expected to communicate their findings and analyses to their superiors, colleagues on different teams, and company stakeholders who may or may not understand complex statistical jargon. In a comprehensive and simply digestible manner, a data scientist will need to describe what they've discovered, how they know they've discovered it, and what needs to be done now that the knowledge is known. It's not always a simple task.

A data scientist could be extracting data from a database, preparing it for various studies, designing and testing a statistical model, or creating reports with easily understood data visualisations on any given day. While data science projects and duties differ per company, there are several basic job activities that are shared by all data science professionals, such as:

1. Gathering large amounts of data and transforming it to a format that can be analysed.

2. Using data-driven strategies and technologies to solve business-related difficulties.

3. Data collecting and analysis using a number of programming languages and algorithms.

4. Using analytical approaches and tools to gain a wealth of knowledge.

5. Using great data visualisations and detailed reports to communicate findings and offer advise.

Discover Data Science has compiled a complete career guide that you can explore by area of specialty if you want to learn more about what a career in data science includes. If you're still debating whether or not to pursue a career or study in data science, consider the following top 5 reasons to do so.

1. Growing Demand

For much of the last decade, data science has been recognised as one of the most in-demand industries, and it shows no signs of slowing down in 2021. Indeed, the US Bureau of Labor Statistics predicts a 27.9% increase in data science jobs from 2016 to 2026. In 2018, LinkedIn estimated a nationwide shortage of over 151,000 data scientists, primarily in the New York City, San Francisco, and Los Angeles metro areas.

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6. Who is eligible for data science?

So, what is it about data science that makes it such a sought-after profession? Consider the world's most powerful and important corporations. It's a safe bet that you came up with names like Amazon, Google, Apple, or Facebook, which all rely heavily on data-driven decision making.

2. Have a Significant Impact on Your Business and the Environment

The opportunity to make an impact through data science is even greater on a global scale. People who haven't had much experience with the profession may believe it's just a glorified number cruncher. While there will be some of that in the usual day-to-day, data science outcomes have far more potential utility than previously thought. As a data scientist, your impact on the world is mostly determined by your interests and the field in which you want to build a name for yourself.

Are you passionate about combating climate change's terrible effects? As a data scientist, you could be helping to save lives by developing more accurate climate models and weather prediction technology, or you could be working on cutting-edge public transit initiatives that reduce CO2 emissions. Do you want to contribute to the fight against hunger? You might look into agricultural techniques and crop yields in order to assist farmers in increasing their food production. This can assist small family farms in saving money and maintaining a viable business. Data scientists work to combat cancer, prevent blindness, discover new pharmaceuticals and medical technology, and empower impoverished countries.

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