How can I become a data scientist? Cost, Salary, Career

Your big horn-rimmed glasses and nerdy appearance may point you toward a career of great importance: data science. Given how data is changing the world and the data scientist’s salary, you should consider becoming a data scientist.


But first, you need to learn how to get the right data science degree and the programs that will prepare you for the rewards of working in data science.


From the early 21st century to the present, Data Science sits comfortably as one of the hottest careers in the world. Data scientists are paid appetizing salaries, and job growth is good. The world is generating more and more data every day that needs to be collected and analyzed by data scientists for several productive purposes.


So in this post, we’ll show you how to become a data scientist. You’ll see what academic programs and degrees you need, and how much it will cost you to become a data scientist. We’ll also show you the types of jobs you can get with your degree, and answer other questions you may have about this topic.


What is data science?

Data science is the disciplinary field that gives birth to data scientists. It is an interdisciplinary field that trains professionals to extract ideas and knowledge from structured and unstructured data.


So, as a multidisciplinary field, data science draws knowledge from mathematics, statistics, computer science, and information science, in particular, it combines statistics, data analysis, and machine learning together with appropriate techniques for understanding and analyzing data.


Because of its close relationship with these other disciplines, it has become difficult these days to distinguish data science from business intelligence, business analytics, predictive modeling, and statistics. People (professionals and novices alike) now use any of these interchangeably.


In addition, the concept of data mining and big data coincides with the concept of data mining, which is why some universities offer their data science programs under the name “Big Data.”


So you see, data science deals with big data analytics using computer programming and virtual mining techniques.



Who is a data scientist?

A data scientist is simply a Data Science tool. How does that sound? Not good enough. So, let’s break down the human terms.


A data scientist is a person (a professional) who collects and analyzes data using his or her interdisciplinary knowledge to find a solution. Consequently, he or she must have the statistical knowledge and computer skills needed to solve complex problems.


In addition, the data scientist will use mathematical and algorithmic methods to solve some of the more analytically complex business problems. It is for this reason that a data scientist is a treasure for large companies and companies looking to expand their operations.


The data scientist’s primary function is to sift through the values of both structured and unstructured data that his or her organization receives. Thus, you will find that the data scientist either extracts data from the database, prepares data for various analyses, builds and tests a statistical model, or creates reports that management can understand through data visualization.


So, typically, a data scientist will do the following:


  • Gather data.
  • Prepare the data
  • Perform exploratory data analysis (EDA)
  • Evaluate and interpret EDA results
  • Build models
  • Test models
  • Unfold models
  • Optimize models.


What skills should a data scientist have?

It’s not enough to get the right education for data scientists (which we explained here) or understand what they do on a daily basis. Without a certain skill set, you can’t succeed in this profession.


So what skills should you have?

These are:

  • Proficiency in computer programs and languages. You should be familiar with SAS, SPSS, MATLAB R, Python, Java, C / C ++, the Hadoop platform, SQL / NoSQL databases.
  • Business acumen or savvy. Since you will have to work in a variety of business environments, you need to gain more than a basic knowledge of the field. This will help you solve complex problems and find solutions that fit your company’s goals.
  • Communication skills. You definitely know how to communicate with data, but people will depend on you to communicate your findings and decisions with them in a language they understand. You should be able to clearly translate your technical findings and analyses to the non-technical departments of the organization you work for.
  • Advanced technical skills. Your skills in math, statistics, machine learning tools, data mining, data cleaning, data visualization, and unstructured data methods should be out of this world.


What is the difference between Data Scientist and Data Analyst?

One word is used all the time when we describe what data scientists do. That word is “analyze.” Data Scientists collect and analyze data, and it’s true. But data analysts also collect and analyze data. So, does that make a data analyst a data scientist?


This is the main question behind the Data Science vs Data Analytics argument. How is a data scientist different from a data analyst?


Here it is:


Data analysts study large data sets to identify trends, develop charts and create visual presentations that help businesses make better strategic decisions. On the other hand, data scientists design and create new processes to model and produce data using prototypes, algorithms, predictive models and custom analysis.


So, you see, while the analyst uses existing methods to perform his or her duties, the scientist develops new processes and methods to facilitate data analysis.


In addition, data analysts are proficient in SQL in their day-to-day work. They can tell a story based on data with some level of scientific curiosity. A data scientist, on the other hand, has a solid foundation in modeling, analytics, mathematics, statistics and computer science in addition to possessing all the skills of an analyst. He uses these to better communicate his findings to business stakeholders to influence their approach to solving business problems.


In addition, while the data analyst will solve the questions the business asks him or her, the data scientist will formulate questions whose solutions are likely to benefit the business.


Where does a Data Scientist work?

Data Scientists find work in any workspace that uses data for work – this applies to any organization that is looking to grow. However, they are more concentrated in commercial enterprises with marketing departments, and in economic sectors such as automotive or insurance.


Another work environment where you’ll find data scientists is at the Department of Defense. Here they help analyze the threat levels threatening the country.


What other jobs can a data scientist fill?

Because of the interdependent nature of data science, data scientists can find jobs in other related fields. This is especially true if you advance in your career by earning a Master’s degree in data science or other related fields.


Here are some of the job roles data scientists can take on:


Data Engineer.

Data Scientists use large amounts of data to develop software. In most cases, they create the architecture that allows data scientists to do their jobs effectively. They also manage database systems, scale data architecture across multiple servers, and write complex queries to navigate data. Consequently, they are fully accustomed to programming languages such as Python, Hadoop-based technologies such as MapReduce, and database technologies such as MySQL.


On data analytics.

Data analysts are professionals who use data to create reports and visualizations that better explain the ideas in the data. Specifically, data analysts help the company they work on understand specific queries through charts. The best way to look at data analysts is the little brother of data analysts. Their expertise is the foundation for academics.


Machine Learning Engineer.

Machine learning engineers create, implement and manage machine learning projects using programming languages such as Python or C / C ++. To get these professionals started in their careers, they may have to start with a background in software development and then continue to gain knowledge in statistics and machine learning.


Computer Scientist and Information Scientist

Computer scientists develop computer technology as well as create new and more efficient ways to use existing technology. You will find them working for the federal government of nations and in computer systems engineering companies.


What are the salaries and job prospects of data scientists?

You only need to ask an honest data scientist to get excited about their pay. But since you may not have one, we’ll tell you how much they make.


According to the Bureau of Labor Statistics (BLS)Scientists working in computer and data science make an average of $118,370 a year. We know that this position is different from Data Scientist. However, both are in the same field and are very closely related, and they are the ones who recognize BLS.


Meanwhile, for computer and data scientists, 31,700 positions were available in 2018. In addition, the estimated job growth rate is 16% from 2018 to 2028, which is much faster than the average job growth rate.


The BLS also provides salary and job growth information for another related position, Mathematicians and Statisticians. According to the BLS, Mathematician and Statistician earn an average of $88,190 per year, and job growth is estimated at 30%


Fortunately, we have a more specific salary for Data Scientists through Glassdoor, Glassdoor estimates Data Scientists earn an average of $120,495 per year. This projection is even higher than the BLS estimate for Data Scientists.


Glassdoor further breaks down this salary for Data Scientists by company as follows:


  • Facebook data scientist salary – $145,365.
  • IBM  data scientist salary – $114,635
  • Microsoft data scientist salary – $129,917
  • Uber data scientist salary – $125,672
  • Apple data scientist salary – $137,560
  • Airbnb data scientist salary – $140,312
  • Google data scientist salary – $140,212
  • Amazon data scientist salary – $120,407
  • Twitter data scientist salary – $142,665
  • LinkedIn data scientist salary – $128,957

read also : data science for all : what is data science

What are the educational requirements for data scientists?

To begin your career as a data scientist, you must acquire at least a four-year Bachelor’s degree from an accredited college. The most preferred undergraduate degree is a Bachelor of Science in Data Science. Fortunately, some schools in the United States offer a Data Science degree.


However, if you can’t get a bachelor’s degree in data science. A degree in an appropriate discipline will do. Such disciplines that will allow you to pursue a career in Data Science include Computer Science, Statistics, Physics, Social Science, Mathematics, Applied Mathematics and Economics.


After earning your bachelor’s degree in engineering, you should pursue a master’s degree in data science. The master’s degree is relevant because most employers prefer those with a master’s degree over those with a bachelor’s degree. Also, the proportion of professionals with a master’s degree is higher than those with a bachelor’s degree.


You can pursue a doctorate in data science after completing a master’s program. However, this is ideal if you aspire to take a leadership position in the field or to teach it at a university.


So, to summarize, the minimum educational requirement to become a data scientist is a four-year bachelor’s degree in data science or a related technical discipline. Meanwhile, to improve your chances of getting a job in data science, you need a master’s degree in data science. Then you should get a Ph.D. degree if you aspire to a leadership position in that field.


Where can I get the best education for data scientists?

Although a bachelor’s degree is the minimum requirement to get a job in data science, we will discuss a master’s program here.


The reason for this is clear. There are more opportunities in data science for masters than for bachelors.


So, when you’re thinking about getting a master’s program in data science, you should consider your options for accreditation, program structure, cost, financial aid, and concentration.


A master’s program in data science may have accreditation from the Accreditation Board for Engineering and Technology (ABET), but it’s not that important. As long as the school has institutional accreditation, she’s fine.


The best data science master’s programs on campus

So, given the checklist above, here are the best master’s programs in data science.



DePaul offers one of the best master’s degrees in data science in the United States. His Master of Science in Data Science has four tracks: computational methods, healthcare, hospitality and marketing. The program also costs $865 per credit hour.

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University of Rochester

Another university where data scientists can also get one of the best master’s degrees in data science is the University of Rochester. This program focuses on computational and statistical methods, health and biomedical sciences, and business and social sciences and costs XNUMX $55,952.


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New York University  ( NYU ).

NYU’s master’s degree for data analysts is also commendable. The MDDS program offers concentrations in big data, math and data, natural language processing and physics. However, tuition is $1,856 per credit.


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Carnegie Mellon University.

Carnegie Mellon’s master’s degree for data scientists is a master’s degree in computational data science. It is a commendable program focused on systems, analytics, and human-centered data science. However, the program costs XNUMX $25,750.


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Columbia University.

Columbia University’s master’s program for data analysts is another of the best programs in the U.S. with its many concentrations. Some of the concentrations that Columbia University offers include computing for data science, cybersecurity, and financial and business analytics. However, the program costs $2.104 per credit.


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Thus, you should also be on the lookout for school and program accreditation, program structure, cost, financial aid, and concentration options.


The best online master’s programs in data science


Thus, you should also keep a close eye on school and program accreditation, program structure, cost, financial aid, and concentration options.


With that in mind, here are the best online data science master’s programs for data scientists.


University of Notre Dame.

The University of Notre Dame in Indiana offers one of the best online master’s programs in data science in partnership with AT&T. This online MS in Data Science program is a 30-credit program that costs $52,000 for 21 months.


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Southern Methodist University (SMU)

Southern Methodist University (SMU) in Dallas is another place where data scientists can get a quality master’s program in data science. SMU’s online master’s in data science focuses on machine learning; business analytics and costs $57,084 XNUMX for the entire program.


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Worcester Polytechnic Institute

Worcester Polytechnic Institute also offers an excellent online MS in Data Science program for data scientists. This master’s program takes 2 years to complete in 33 credit hours and costs $1,566 per credit hour. So, expect to spend $51,678 XNUMX in tuition.


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Indiana University (IU) Bloomington

Indiana University (IU) in Bloomington also offers a popular online master’s program for data scientists. Its online data science majors specialize in data analytics and visualization, intelligent systems development, precision health care and cybersecurity. This is a 30-credit course that costs $1,498.01 per credit hour.


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Regis University.

Regis University in Denver, Colorado, is a Roman Catholic university offering a quality online master’s program in data science. Its MS in Data Science seeks flexibility, if nothing else. Meanwhile, this credit hour 36 course costs $820 per credit hour or $29,520 for the full program.


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You can also check out these 40 Best Data Science Programs


How much does it cost to become a data scientist?

Becoming a data scientist is pretty expensive. With salaries this impressive, you wouldn’t expect tuition to be cheap, otherwise everyone would become a data scientist.


So, depending on the level of education required to become a data scientist, a bachelor’s degree in data science will cost an average of $40,940 XNUMX for a public college per year. This cost includes tuition; room and board; books and supplies; transportation; and other expenses.


You should expect an average of about $50,900 for private four-year colleges in the United States.


Over four years, you’d spend $163,760 for a bachelor’s degree at a public university and $203,600 at a private university.


Meanwhile, a master’s degree in data science (online and on-campus) costs between $25,750 $55,952 and $40,851 XNUMX, based on an analysis of our top programs. The average of these numbers yields XNUMXXNUMX dollars for the duration of the program.


Consequently, you should expect to spend between $204,611 and $244,451 on education for data scientists at public and private institutions, respectively.


How can I become a data scientist?

Now you know the educational requirements to become a data scientist and how much it will cost. So, what steps should you take to become a data scientist?


To become a data scientist and get a real, cool paycheck, here’s what you must do:


Start training.

First and foremost, you must be confident that you want to become a data scientist. Once you have that confidence, start acquiring skills before you even go to university. Start learning the programming languages used by data scientists, such as Python, Java, and R. Also, continue to update your knowledge of applied mathematics and statistics. You will find them useful not only in college, but also in your future work.



Get a bachelor’s degree

This is a prerequisite for getting a job as a data scientist, so it’s very important. Get a bachelor’s degree in data science if you can find schools that offer it. If not, get a bachelor’s degree in statistics, mathematics, or information technology. Continue to study programming languages while you’re in college to get your bachelor’s degree. Also, look for internship opportunities that will help you start building a strong network in this field.


Get a job.

With a bachelor’s degree, you will be able to get a job. This will be an entry-level job that you may pay less for than we anticipated, but that’s okay. If you have certifications in related fields, your chances of getting an entry-level job as a data analyst or scientist are higher. So, consider certifications in business intelligence applications, relational database management systems, and data visualization software.


Get a master’s degree.

You will grow faster in this field if you have a master’s degree. Many employers are looking for data scientists with a master’s degree and industry experience. Consequently, not only should you get a master’s degree, but you should also know how to use enterprise-level data management software such as Hadoop, MapReduce, and Spark. Well, most master’s programs include the use of these programs in their curricula.


Continue learning

One of the downsides of a Data Science career is that it is constantly changing. A program you can’t do without today will be obsolete tomorrow. Consequently, you need to stay current in this ever-evolving field.


You can do this by taking continuing education courses that are relevant to the present. You can also stay current in this field by networking and attending educational and professional development opportunities through boot camps and conferences.


Tips on how to get a job in data science

Remember that one of the steps to becoming a data scientist is to get a job? Yes, it’s important to get a job and get actual work experience. However, it can be difficult to get a job, especially as a new graduate.


So, to make your job search easier, here are some tips for you:


  • Create a strong portfolio. This is very important to successfully get a job in data science. To create a portfolio, you must have relevant experience that will enhance your educational credentials. If you have completed projects, highlight the best ones by focusing on the larger ones.
  • Get a mentor. A mentor is very important. This is a way of networking that will benefit you because a mentor with years of experience in the industry will be able to tell you exactly what companies are looking for.
  • Attend conferences and meetings. Still making connections that will help you easily enter the industry, attend conferences. Look for data science conferences and attend. Some conferences to consider include the Strata Data Conference, KDD (Knowledge Discovery in Data Mining) and the International Conference on Machine Learning (ICML). You should also consider meetings like, SF Data Mining and Data Science DC.
  • Use message boards. You need to look for jobs, and even though meetings will likely expose you to job openings firsthand, you’ll still need job boards. Consider job boards like Kaggle, Datajobs, and Central Data Science.
  • Do the data science interview. The data science interview includes the following sequence: phone screen, home appointment, call with hiring manager, on-site interview with hiring manager, on-site interview – technical call, and on-site interview with the Postmaster. Prepare well for each stage and conduct the interviews.



With an average annual salary of $120,495,204,611, data scientists are the best professionals in the country. But the education to become a data scientist is just as expensive as education in other professions. It costs an average of XNUMX XNUMX dollars to get a bachelor’s and master’s degree (which is the important degree you need) to become a data scientist.


It is for this reason that you need to choose an affordable data science degree program while becoming a data scientist. We believe that with this post, you will be able to pave your way to a successful career in data science.

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