{"id":1847,"date":"2020-01-11T00:54:04","date_gmt":"2020-01-11T00:54:04","guid":{"rendered":"http:\/\/michaelleander.me\/?p=1847"},"modified":"2021-08-30T13:54:53","modified_gmt":"2021-08-30T13:54:53","slug":"why-choose-data-science-as-a-career","status":"publish","type":"post","link":"https:\/\/michaelleander.me\/why-choose-data-science-as-a-career\/","title":{"rendered":"Why Choose Data Science as a Career"},"content":{"rendered":"\n<p>Data Science has recently become one of the most talked-about technologies in the 21st Century. <\/p>\n\n\n\n<p>While many people may decide that they want to become a data scientist, it&#8217;s a buzzword that many of them may not truly understand<\/p>\n\n\n\n<p>Wikipedia defines Data Science as &#8220;a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.&#8221; <\/p>\n\n\n\n<p>In other words, Data Science is a buzzword that uses scientific methods to find solutions to common everyday problems.<\/p>\n\n\n\n<p>Data Science as a career is about extracting both structured and unstructured data. The roots can be based on statistics, mathematics, and even computer science. <\/p>\n\n\n\n<p>Data are then broken down into manageable pieces. These pieces are analyzed, visualized, managed, and then stored. <\/p>\n\n\n\n<p>Eventually, the data are passed on to companies so their management can use it to make accurate, long-range, data-driven decisions.<\/p>\n\n\n\n<p>Data Science is one of the most sought-after jobs in today&#8217;s employment market. There are large numbers of positions available in many different industries. <\/p>\n\n\n\n<p>Employers are eager and willing to pay employees very lucrative salaries to bring in qualified applicants who can help them be successful in their businesses.<\/p>\n\n\n\n<p>In this article, we\nwill cover some of the pros and cons about choosing Data Science as a\nprofession. Our goal is to provide you with as many of the necessary insights\nas possible so you can decide for yourself whether it should be your future\ncareer.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The\nPros<\/h2>\n\n\n\n<p>Data science has created a huge impact on practically all 21st Century industries. The demand is huge. Experts say that the <a href=\"http:\/\/michaelleander.me\/how-data-analytics-can-transform-your-business\/\">data analytics market<\/a> will evolve to be at least 1\/3 of the global IT market in the next few years.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1.\nPlenty of Opportunities<\/h3>\n\n\n\n<p>Both large and small\nbusinesses and organizations are looking for new employees with two objectives:<\/p>\n\n\n\n<ul><li>They must be able to synthesize data, and<\/li><li>They should then be able to communicate their findings in ways that will help their company make the right decisions so that <a href=\"https:\/\/michaelleander.me\/how-data-analytics-can-transform-your-business\/\" data-type=\"URL\" data-id=\"https:\/\/michaelleander.me\/how-data-analytics-can-transform-your-business\/\">data analytics can transform their business<\/a>.<\/li><\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">&nbsp;2. Career Growth<\/h3>\n\n\n\n<p>There is a tremendous shortage of data scientists at all levels of the employment chain. The IT industry is constantly on the verge of change. <\/p>\n\n\n\n<p>Many middle-level managers and professionals now find their career growth is stagnant. <\/p>\n\n\n\n<p>Data Science is their best option to overcome many of the downturns of career stagnation.<\/p>\n\n\n\n<p>Among the biggest trends of data analysis today are in the banking and e-commerce sectors. <\/p>\n\n\n\n<p>Data analysis will continue to be needed in the marketplace creating secured jobs for future data scientists.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3.\nExcellent Pay<\/h3>\n\n\n\n<p>Data Science is one of the highest paying jobs in the business world today. Average salaries can exceed $100,000 a year. <\/p>\n\n\n\n<p>Annual pay hikes have recently been 50 percent higher than most other IT professions. Salary trends for data science professionals nearly ensure positive and exponential growth.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. Work\nOptions<\/h3>\n\n\n\n<p>Data scientists can work nearly anywhere in the world and in almost any industry or domain. Jobs available range from financial services to marketing and sales, health care, pharmaceuticals, consulting firms, and the retail industry. <\/p>\n\n\n\n<p>There are data scientist positions available with the government and non-governmental organizations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5.\nExperience is not a Factor<\/h3>\n\n\n\n<p>The field of Data Science is so new that many organizations have not yet decided on how to construct the correct experience profile. <\/p>\n\n\n\n<p>This provides a great opportunity for IT professionals to up-skill and learn data science in a new field.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">6. Lack\nof Competition<\/h3>\n\n\n\n<p>There is currently a\nshortage of data scientists since the field itself is relatively new.&nbsp; The experience gap between entry-level data\nscientists and experienced professionals is only a few years. This provides an\nenormous opportunity for career growth.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">7.&nbsp; Ease of Job Hunting<\/h3>\n\n\n\n<p>Data scientists are in higher demand than ever before. There is also a shortage of skilled professionals in the market. <\/p>\n\n\n\n<p>This situation makes it relatively easy to search for jobs in the data science domain.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">8.\nTraining Options<\/h3>\n\n\n\n<p>There are numerous training options available for students to study data science. The different modes include training online, classroom, and even self-paced videos. <\/p>\n\n\n\n<p>University degrees are available in both postgraduate and masters programs.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The Cons<\/h2>\n\n\n\n<p>Even though Data\nScience can be a very lucrative career option, a few disadvantages do exist.\nHere are some of the limitations:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1. The\nDefinition is Blurred<\/h3>\n\n\n\n<p>Because <a href=\"https:\/\/towardsdatascience.com\/a-beginners-guide-to-data-science-55edd0288973\">Data Science<\/a> is so new, in some cases it may not have achieved a fully-understood definition. <\/p>\n\n\n\n<p>Some employers can have trouble writing down the exact meaning of what a Data Scientist is.<\/p>\n\n\n\n<p>The specific role of a Data Scientist often depends on the field that the company specializes in. <\/p>\n\n\n\n<p>While some may describe Data Science as the paradigm of Science, some critics consider it a simple re-branding of Statistics.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2.\nMastering Data Science is Difficult<\/h3>\n\n\n\n<p>Data Science is actually a mixture of several different fields. It stems from Statistics, Mathematics, and Computer Science. <\/p>\n\n\n\n<p>It&#8217;s almost impossible to master each of these fields and be an expert in every one of them.<\/p>\n\n\n\n<p>A person with a background in Statistics will not usually be able to master Computer Science on short notice to become proficient in Data Science. <\/p>\n\n\n\n<p>In such an ever-changing dynamic field, employees may need to continue to study different avenues of Data Science.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3.\nExtensive Domain Knowledge<\/h3>\n\n\n\n<p>Another disadvantage of Data Science is that it depends on Domain Knowledge. <\/p>\n\n\n\n<p>A person with a background in Computer Science and Statistics can have difficulty solving an intricate Data Science problem without the proper background.<\/p>\n\n\n\n<p>The same is true for someone working in the health-care industry. <\/p>\n\n\n\n<p>If they are analyzing genomic sequences, they need to have some knowledge of genetics in addition to molecular biology. This gives the data scientist the capability to properly assist the company. <\/p>\n\n\n\n<p>But, if they have a different background, it&#8217;s difficult for them to be effective in a completely different industry.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4.\nUnexpected Results<\/h3>\n\n\n\n<p>When a data scientist analyzes data to aid their employer to make decisions, the data can often yield arbitrary or even unexpected results that don&#8217;t apply to the employer&#8217;s situation. <\/p>\n\n\n\n<p>This can also happen when management doesn&#8217;t understand how to apply the data or when they are unable to properly utilize their current resources.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5. Data\nPrivacy<\/h3>\n\n\n\n<p>When data scientists help companies make decisions, the data provided may intrude on the privacy of their customers. <\/p>\n\n\n\n<p>If a client&#8217;s personal data are visible to the company, data leaks can occur during the discovery process. <\/p>\n\n\n\n<p>This lapse in security can be a major concern for many industries.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Conclusion<\/h3>\n\n\n\n<p>While the field of\ndata science may have many lucrative advantages as a career choice, there can\nbe some disadvantages. Data Science is a promising, high-paying, and\nrevolutionary field. It is also continuing to evolve and may take many more\nyears for the student to gain proficiency.<\/p>\n\n\n\n<p>We hope that by\nweighing the information we&#8217;ve provided, you will be able to make the right\nchoice about whether or not Data Science should be your career choice. A\nprofessional in the 21st Century, with the analytical skills of a data\nscientist, should be able to master the ocean of Big Data in the 21st Century.\nIf they do, they will likely become a vital asset to any business or\norganization, boosting the company&#8217;s business interests and their own career.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Science has recently become one of the most talked-about technologies in the 21st Century. While many people may decide that they want to become a data scientist, it&#8217;s a buzzword that many of them may not truly understand Wikipedia defines Data Science as &#8220;a multidisciplinary field that uses scientific methods, processes, algorithms, and systems [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1848,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[107],"tags":[],"yst_prominent_words":[114,121,117,116,95,84,108,115,110,120,109,123,119,112,118,111,124,122,113],"_links":{"self":[{"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/posts\/1847"}],"collection":[{"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/comments?post=1847"}],"version-history":[{"count":0,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/posts\/1847\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/media\/1848"}],"wp:attachment":[{"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/media?parent=1847"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/categories?post=1847"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/tags?post=1847"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/michaelleander.me\/wp-json\/wp\/v2\/yst_prominent_words?post=1847"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}