Everything You Need to Know About Becoming a Data Scientist

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What Is a Data Scientist?

A data scientist is often referred to as an analytical data expert. This type of scientist spends his or her time solving complex problems using various sources of data. A data scientist will also use his or her skill set to predict certain problems and create solutions before the problems actually occur. To put it simply, a data scientist is a “trend-spotter, mathematician and a computer scientist” combined into one person. Because it takes a very unique set of skills to be a data scientist, those entering this line of work will find they are highly sought-after as well as generously paid for their services.

Years ago, becoming a data scientist wasn’t that heard of. Thanks to advances in technology, though, all industries are finding they can greatly benefit from employing data scientists. These types of professionals take unstructured data and feed it into databases, followed then by using analytics to making meaningful use of the data. Businesses can then take the data┬áto gain in-depth insights into their operational processes, which leads to more effective and efficient practices.

If you are wanting to become a data scientist, there are certain skills and credentials you will need. Let’s take a look at what you need to know.

How to Become a Data Scientist?

Many data scientists actually start out under a different title, such as a data analyst or statistician. Big data has revolutionized data science, and the careers of data analysts and statisticians have evolved as well. Many academic institutions have recognized the need for data scientists and have added programs to their available curriculums. In fact, the United States boasts more than 60 higher education programs for those who want to become a data scientist.

To become a data scientist, you basically have three educational paths to choose from.

  1. The first educational path consists of going to college and earning a degree or graduate certificate. Degree programs provide a structured environment for you to take part in internships as well as network with other professionals working as data scientists. Furthermore, degree programs provide you with an extensive amount of knowledge relating to data science.
  2. The next path you can follow to become a data scientist involves taking MOOCs (self-guided online classes that are free of charge and offered to the public). This path enables you to complete projects according to your own schedule and it allows you to structure an academic path that best fits your lifestyle. Unfortunately, though, some employers will not recognize the classes you take as formal education.
  3. Boot camps make up the third educational path you can follow to become a data scientist. Like MOOCs, some employers won’t recognize the boot camps as formal education, but there is no denying you will learn very valuable knowledge relating to data science.

If you want to follow an educational path that is going to impress employers, it is suggested to earn a degree in data science. On the side, however, and at your own convenience, you should complete as many boot camps and MOOCs as possible. You will be adding to the knowledge you learn while earning a degree, and this can prove to be of the utmost advantage when applying for jobs after graduation.

What Skills Are Needed to be a Data Scientist?

There are seven primary skills that successful data scientists are distinguished in. Generally, these skills come somewhat natural to most data scientists, however, formal education, such as earning a degree, can refine these skills and lead to advances in data science practices. Here is a look at the seven skills of successful data scientists:

  1. Machine learning: Machine learning skills are especially needed by data scientists working for large companies that have access to massive amounts of data. Familiarity with R and Python libraries is a plus when mastering machine learning skills.
  2. Programming: You will need to be well-versed in a variety of programming tools and database querying languages. You may even be required to create different querying languages.
  3. Statistics: Being distinguished at statistics is a huge plus for a data scientist, especially if you can easily identify which statistical techniques are the most appropriate to apply to various complexities.
  4. Data wrangling: Data wrangling involves taking unstructured data and making meaningful use out of it. As part of data wrangling, you will likely be responsible for pinpointing missing values and other types of data imperfections.
  5. Multivariable calculus and linear algebra: Your multivariable calculus and linear algebra methods are going to prove beneficial when working with algorithms and predictive performance analytics.
  6. Software engineering: Any software engineering experience that you have will give you a head start toward becoming a successful data scientist.
  7. Data visualization and communication: You will use your data science skills to present data visualizations. You will use these visualizations to communicate whey your data science theories are effective in producing enhanced operational efficiency. These skills can be refined by becoming familiar with various software programs that work with visually-encoded data.

What Is the Average Annual Salary for a Data Scientist?

According to Glassdoor.com, out of 2,951 data scientist salaries submitted to its platform, the average annual payout is $120,931. The platform also recognized additional cash compensations given to data scientists, which was an average of $11,772 a year. As you can see, data scientists earn a very comfortable salary.

It is pertinent to understand that when applying for data science jobs, you will likely have to choose between different position levels. Generally, you will choose between the following:

  • Junior data scientist
  • Mid-level data scientist
  • Senior data scientist

A junior-level data scientist position is ideal for someone who has just graduated with a degree or from a boot camp and who has little experience. A senior data scientist position, on the other hand, is geared more toward someone who has been working three-plus years as a data scientist.

What Schools Offer Programs for Data Scientists?

There are many schools that offer accredited programs to those wanting to become a data scientist. Statistics show, however, that the majority of data scientists have a master’s degree. This means you are going to have spend several years in college to keep up with the competition in this field. In fact, earning a doctorate-level degree will be of the most benefit to your career. Some of the top schools that offer masters-level and/or doctorate-level data science programs include:

  • Syracuse University
  • George Washington University
  • Southern Methodist University
  • American University

Many schools offer data science programs that can be completed completely online. If you are unable to devote all of your time to schoolwork, online programs can be of the utmost value. They allow you to study and complete work according to a schedule that is most convenient for your lifestyle.

The Takeaway

As companies continue to collect large amounts of data, there will be a continuing need for data scientists to make meaningful use out of this data. If you want to become a data scientist, you should start as soon as possible because you will need many years of experience and knowledge to maintain a competitive edge in your career endeavors.

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