The buzz around Data Science continues to grow astronomically. It’s almost monthly that you’ll see an article on Forbes or Indeed discussing how great of a career Data Science is. But just because these websites claim that this is a good job doesn’t mean it’s the best career for you. A lot of factors come into place in deciding whether you should pursue a career in Data Science. Gone are the days when tech jobs were only available at Google and Facebook. Today, almost all industries need to hire tech employees. Companies are drowning in all the tsunamic wave of data which is an invaluable asset for drafting business strategies. As a result, the companies need to hire Data Scientists to be able to manage it, analyze it, and use it to identify, predict and solve problems. With the demand for data-savvy professionals increasing at a faster rate, The McKinsey & Company has projected a global excess demand for 1.5 million new data scientists. By 2018, a projected talent gap of 140,000 to 190,000 qualified data science workers is predicted. According to Glassdoor’s list of best jobs for best Work-Life Balance, the data scientist is the best job in America for 2016. One can expect a median base salary of $116,840, with plenty of job openings available. But what does a work day of a data scientist look like? Are they just confined to an office crunching numbers for the rest of their working life? Not exactly. Data Scientists are constantly trying to predict the future by using numbers. They are working with clients’ or employers problems and replicating models to solve them. What you offer as a data scientist is a comprehensive analysis of the customer’s whole business. This versatility means constant movement and frequent discussions with employees at all levels of your company. So sure, you’ll have a desk with a fancy computer to get the job done, but don’t think of Data Scientists having your stereotypical 9-5 desk job. The Day-to-Day Activities Although we just gave you a pretty decent primer on the buzz around Data Science, we haven’t quite answered the topic of whether or not Data Science is a good career. From the perspective of an outsider, Data Science screams loads of mathematics and science. However, if they would take a look at the job sites, they might be shocked at first to find skill qualities such as ‘works well with others,’ ‘knows how to report and communicate’ as part of the job description. Since the roles of Data Scientists mean working across the board with employees of all levels, it’s crucial that you be able to communicate properly. You might be the only Data Scientists in a company, and many of the people you work with would have no relation to statistics or mathematics for years. Communication is one of the most underrated skills for a Data Science. If you know you're not somebody who enjoys communicating sophisticated and intricate information to the masses, Data Science might not be the best career choice for you. In other situations, Data Science might permeate into individual units. The chances are that you will be working in the marketing department, the product design department and even the sales department. You can expect to solve real life problems by providing practical solutions. One should also be forward-thinking as you will be using a large amount of data to solve real time problems as they are happening. So why are we telling you all of this? One must realize that choosing whether or not Data Science is an excellent career choice goes further than just knowing the science behind it. You must understand all the skills necessary and the day-to-day activities that it encompasses. If you know all the programming and statistics, but can’t properly communicate with others; this might not be the field for you. The Programming So we’ve gone over the outlook and a brief synopsis of the day-to-day activities for a Data Science. In other articles on YDSOA, we’ve touched on some of the programming and sciences that are needed for a successful Data Science career, including our Machine Learning and SQL articles. However, there are some more steps you can take to become familiar with the traditional software you’ll be needing to use for jobs in this field. -R: Let’s start with R. R is one of the best places to start for those looking to get into Data Science for the fact it has a very active community, and the software itself is free to use. R is traditionally used for statistical analysis, but can also be used for data mining and visualization. We’ll be rolling out an introductory post into the workings of R programming, but for now, this a great online course to get your feet wet. -Python: The second language that’s good to have some mastering in is Python. Python is currently one of the most popular programming languages in the world and for good reason. It’s simplicity, and the overwhelming amount of resources create a user-friendly environment. -Perl: Perl was originally built in 1987 by a computer programmer named Larry Walt with the purpose of being able to process and handle massive amounts of text. It showed the most popularity in the 1990’s and although it doesn’t have the following it once had, it still remains a force that has stood the test of time in the world of programming. In addition to its powerful text processing tools such as Regular Expression and other useful abilities, it has several useful add-ons in its repertoire. Besides the big three, I have listed some other languages and tools that would be helpful add-ons. -Scala: The hottest language right now, ideal for working with real-time data. We’ll be touching more on Scala in a later article. -SQL: SQL remains a powerful and easy-to-use programming language, mostly used in database management. Our full SQL introduction can be viewed here. -Excel: Seeing Excel on this list may come as a bit of surprise, but Excel remains one of the most useful pieces of software a Data Scientist can know. Its incorporation with VBA allows the user to conduct some extremely sophisticated analysis. Is Data Science a Good Career? Being that YDSOA focuses primarily on Data Science and Bioinformatics, you could say that we might be a little bias in our overall consensus on whether Data Science is a good career or not. However, we do believe we've presented some strong evidence on how great the opportunities are in the world of Data Science, and what an interesting a career it truly can be. With that being said, you must understand all aspects that go into the job. Sure, knowing the programming and science behind this career is crucial, and you won’t get farther than a job interview without it. However, don’t underestimate the personal and communication side of things. Realize that you’ll be working with people from a broad spectrum and knowing how to communicate with them properly will be crucial.