Data science is a growing field of study that is rapidly gaining popularity in different companies across the world. People are seeing the positive effects of using data science to shape their business decisions.

Before, companies were making decisions blindly, without really knowing what their customers wanted. However, now, any company can gather the data of their customers and figure out a lot of information, including stuff about their likes, dislikes, desires, wishes, fears, needs, and more.

With all this information, a company can shape its sales strategy and grow much faster.

Data science is high in demand and explains how digital data is transforming businesses and helping them make sharper and critical decisions.

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Data analytics work with any machine that has the intelligence to process chunks of data but any professional needs to have skills that will allow them to control said machine. Photo by Kelly Sikkema on Unsplash

In the past, data science existed exclusively as a Master's degree, however, with the years and the development of the field, it has become more than just a Master's degree and students can graduate with other titles.

Students interested in pursuing a career in data science, analytics, programming, or big data, can now pursue a Bachelor's degree or a Master's degree in college.

Depending on what are your plans and projects for the future, you should choose between getting a Bachelor's or Master's degree. For instance, if you want to work full time as a data scientist, then you should graduate with a Bachelor's degree, it makes more sense.

However, if you wish to go into other careers, like computer programming with a focus on data science, then you'll need to graduate with another degree. In this case, we recommend you major in one thing and a minor in another, or get a double degree, and so on.

Knowing the salary of the professionals working in your field of interest is important because it can help you make a decision. For example, the salary is different for each field. Whether that is computer programing, AI intelligence, data science, statistical analysis, algorithms (languages like Python or SQL), or you wish to become a computer engineer.

In this article we are going to tell you about the salary of data scientists depending on your years of experience, what is the standard pay, learning how to manage your finances, and so on.

Are you interested in a career in Data Science?

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Is there a standard salary for a data scientist?

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Data scientists spend years learning the intricate side of this business and every job (analyst, scientist, engineer) takes a long time to dominate. Photo by Samuel Bourke on Unsplash

The simpler answer to this question is yes, there is a standard salary for data scientists and analysts!

However, there are many details to take into consideration. For example, there are different levels of jobs depending on your years of experience and knowledge.

There are entry-level jobs that correspond to professionals who recently graduated from college or have a couple of years of experience. These jobs are usually the beginner level and they are demanding but not complicated.

Then there are mid-level jobs. These jobs are available to any professional who has been working in the field for a while. A data scientist or analyst at an intermediate has usually been working in the business of analysis or analytics for over five years.

Finally, there are experienced data scientists and analysts. People working in the field for over 7 to 10 years are highly experienced and have been managing the same stuff for many years.

Keep in mind that learning to become a data scientist or data analyst will take years of hard work. You are not a machine that will learn things after doing them one time.

Learn about the jobs you could pursue with a major in data science.

What is the salary of data scientists?

If you search online you will find all sorts of information regarding this question. However, the answer is not always precise and there are some factors you should consider. For example, location, minimum wages, living expenses of the area, the success of the company you're applying to, and so on.

Below you will find an approximate salary for each of the levels we mentioned above:

  • Entry-level data scientist - regardless of the influx of early-career professionals, the median starting salary for a data scientist remains as high as $95,000.
  • Mid-level data scientist - the median salary for a mid-level data scientist is $130,000. However, if this professional also has a managerial role, the median salary rises to $195,000.
  • Experienced data scientist - the median salary for experienced data science professionals is $165,000—while the median salary for experienced manager-level professionals is considerably higher at $250,000.
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Data scientists and analysts take time learning programming languages like Python or SQL because every business needs a professional operating the machine. Photo by James Harrison on Unsplash

If you want to have a clear idea of what exactly is the pay for a data scientist in your area, you should research each company, try to talk to them, and find all the information you need.

Is data science a stressful job?

Learn to manage your finances

It doesn't matter if you have a good salary if you're spending most of it every single month. You might as well find a low-paying job that requires less effort and you'd still end up saving the same amount of money every month.

Your finances are supposed to be kept as a life project because your life depends on it!

If you feel like you don't have the skills necessary to help you succeed with your finances, you can always find a professional with enough experience to teach or guide you.

Finance management doesn't require complex skills, especially if you're only managing your own. It's not like data science, where you need to learn to become a computer or software engineer.

Working on your finances should take you a few minutes every single day, but it can have a great impact on your life and your future. This is why people from all fields and careers should develop basic finance skills.

Here are a few tips to help you track your income and expenses better:

  • Find a way to track your expenses - you don't need to be a professional accountant to set up an Excel sheet to track your monthly expenses. There is plenty of other software to help you with this, all you have to do is go online and search for the software that works best for you.
  • Come up with a budget - statistics show that people with monthly budgets have an easier time working up their finances. You should include what you spend on rent, food, transportation, going out, and so on. Learning what are the things you're spending your money on can help you cut back and start saving.
  • Create a savings account - the management of a savings account is not hard at all. All you have to do is talk to your bank and they will pretty much do everything for you.
  • Cut back - learn what are the unnecessary things you're spending money in and cut back. Your amount of cutbacks is as good as your amount of savings.
  • Find help - getting someone to help you with your finance projects can feel like a relief. A professional accountant can give you insight, tips, support, and information.
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If you want to work as a data analyst you should search for a job that offers a project including statistical analysis, systems development, and other well-known fields in data science. Photo by Sigmund on Unsplash

What is data science?

Data science is a field of study dedicated to extracting, analyzing, comprehending, and communicating information.

It is an interdisciplinary field that uses the scientific method, algorithms, systems, and processes to excerpt insight from messy and unstructured data.

The goal of data science is to apply the knowledge extracted into actionable business moves. A company can use data science to understand what its customers want, need, or desire.

Data science uses statistics, data analysis, informatics, and other methods to understand certain problems or phenomena in groups of people and their information.

There's a crossover between data science and math, statistics, information science, computer science, and domain knowledge. However, this does not mean that data science is a form of computer science. These are all different fields that exist for different purposes.

Before the technology era, there were 2 paradigms of science, empirical and theoretical. With technology, a new paradigm emerged, the computational. Finally, with the creation of data, scientists argue that there's finally a fourth paradigm that is data-driven.  Science is constantly changing, especially since the technology was introduced to our world.

Data science is related to data mining, machine learning, and big data. A data scientist is someone who creates programming code and combines it with statistical knowledge to create insights from data.

Learn what are the top universities in the United States for data science.

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