How to become a Data Scientist
skills, courses, career, expectations, salary
From the beginning of the 21st century to the present day data science sits comfortably as one of the hottest careers in the world. Data scientists are getting a delicious salary and the job growth is good. The world is generating more data every day that data scientists need to collect and analyze for various productive purposes.
So in this post, we’re going to show you how to become a data scientist. You will see what types of academic programs and degrees you need and how much it costs to become a data scientist. We’ll also show you the types of jobs you can get with your degree and answer any other questions you might ask about the topic.
What is Data Science?
Data science is the field that creates data scientists. It is a multidisciplinary field where professionals are trained to extract insights and knowledge from structured and unstructured data.
As a multidisciplinary field, data science draws knowledge from mathematics , statistics, computer science and information science . In particular, statistics, data analysis and machine learning are combined with the associated methods to understand and analyze data.
Because of its close relationship with these other disciplines, it is difficult these days to distinguish data science from business analytics, business intelligence, predictive modeling, and statistics. People (professionals and beginners) are now using these interchangeably.
The concept of data mining and big data corresponds to that of data mining, which is why some universities offer their data science programs under the name big data.
You see, data science is about analyzing large amounts of data using computer programming and virtual mining methods.
Who is a Data Scientist?
A data scientist is someone (the professional) who uses their multidisciplinary knowledge to collect and analyze data to provide a solution. Therefore, he must have the statistical and computer skills needed to solve complex problems.
In addition, the data scientist will use techniques in math and algorithm to solve some of the most analytically complex business problems. Because of this, the data scientist is a treasure trove for large corporations and companies that are ready to grow their business.
The main function of a data scientist is to sift meaning out of both the structured and unstructured data that his organization receives. In this way, the data scientist either extracts data from a database, prepares the data for various analyzes, creates and tests a statistical model, or creates reports that management can understand using data visualizations.
Therefore, in general, the data scientist will do the following:
- collect data
- Prepare data
- Perform exploratory data analysis (EDA)
- Evaluate and interpret EDA results
- build models
- Test models
- Deploy models
- Optimize models.
What skills should a data scientist have?
It is not enough to have the right education to be a data scientist (which we explained ( you can click right here for the knowledge base ) or understand what they do on a daily basis. Without a specific skill you may not be able to do this job.
So what are these skills that you must possess?
Here you are:
- Expertise and language skills in computer programs and languages. You must be familiar with SAS, SPSS, MATLAB R, Python, Java, C / C ++, Hadoop Platform, and SQL / NoSQL databases.
- Business acumen or skill. Since you will work in a variety of business environments, you will need to acquire more than just a basic understanding of the business industry. This allows you to solve complex problems and create solutions that are aligned with your company’s goals.
- Communication skills. You definitely know how to communicate with data, but people will depend on you to communicate your insights and solutions to them in a language they would understand. You need to be able to clearly translate your technical findings and analysis into the non-technical departments of the organization in which you work.
- Advanced technical skills. Your knowledge of math, statistics, machine learning tools, data mining, data cleansing, data visualization, and unstructured data techniques should be out of this world.
What is the difference between a data scientist and a data analyst?
One word comes up all the time when describing what data scientists do. That word is “analyze”. Data scientists collect and analyze data, that’s right. But data analysts also collect and analyze data. Does that make the data analyst into a data scientist?
This is the core question behind the argument data science vs. data analytics. How does the data scientist differ from the data analyst?
Here it is for everyone:
Data analysts examine large amounts of data to select trends, develop charts, and create visual presentations that help organizations make better strategic decisions. Data scientists, on the other hand, design and engineer new processes for data modeling and production using prototypes, algorithms, predictive models, and custom analytics.
You see, while the analyst is using pre-existing techniques to accomplish his or her duties, the scientist is developing new processes and techniques to simplify data analysis.
In addition, data analysts are proficient in SQL in their routine work. You can tell a story from data with a certain amount of scientific curiosity. On the flip side, the data scientist not only has all of the analyst’s skills, but also has a solid foundation in modeling, analytics, math, statistics, and computer science. He uses this to better communicate his results to relevant stakeholders in the company and to influence the way in which they approach a business challenge.
While the data analyst answers questions posed by the company, the data scientist formulates questions whose solutions are likely to benefit the company.
Where does a data scientist work?
Data scientists find employment in any area of work where data is used to operate – in any organization that seeks to grow. However, they focus more on business activities with marketing departments as well as branches of the economy such as automotive or insurance.
Another work environment you can find data scientists in is the Department of Defense. Here they help in analyzing the threat levels of a nation.
What other tasks can a data scientist take on?
Because of the interdependence of data science, data scientists can find jobs in other related fields. This is especially true as you progress in your career by completing a Masters degree in Data Science or other related fields.
Here are some of the tasks data scientists can do:
Data engineer
Data engineers use large amounts of data to develop software. For the most part, they set the architecture that data scientists can use to perform their tasks effectively. They also manage database systems, scale the data architecture across multiple servers, and write complex queries to navigate through the data. As a result, they are fully used to programming languages like Python, Hadoop-based technologies like MapReduce, and database technologies like MySQL.
Data analyst
Data analysts are experts who use data to provide reports and visualizations that better explain the insights contained in the data. In particular, data analysts help the company understand certain queries with charts. The best way to look at data analysts is through the data scientist’s little brother. Your expertise is the basis for the scientist.
Machine learning engineer
Machine learning engineers create, implement, and manage machine learning using programming languages such as Python or C / C ++. In order for these professionals to begin their careers, they may need to have a background in software engineering and then gain knowledge of statistics and machine learning.
Computer and information researcher
Computer scientists design computer technologies and create new and better uses for existing technologies. You can find them in the federal government and in companies that design computer systems.
What is the salary and job prospect of data scientists?
All you have to do is ask an honest data scientist to be happy about their payment. But since you might not have one, we’ll tell you what they deserve.
According to the Bureau of Labor Statistics (BLS), Computer and information research scientists earns an average of $ 118.370 per year. We know that this job role is different from that of a data scientist. However, both are in the same field and very closely related, and they are the ones that the BLS recognizes.
Fortunately, we have a more specific salary for data scientists through Glassdoor . At Glassdoor, the average earnings of a data scientist is $ 120.495 per year. This forecast is even above the BLS estimate for computer scientists and information researchers.
Glassdoor provides the following company data scientist salary breakdown:
| Facebook – $ 145,365 IBM – $ 114,635 Microsoft – $ 129,917 Uber – $ 125,672 Apple – $ 137,560 | Airbnb – $ 140,312 Google – $ 140,212 Amazon – $ 120,407 Twitter – $ 142,665 LinkedIn – $ 128,957 |
What are the training requirements for data scientists?
To begin your career as a data scientist, you must complete at least four years of undergraduate studies from an accredited college. The most preferred undergraduate degree is the B.Tech in Data Science. Fortunately, some schools in the US offer a data science degree.
However, if you cannot get a bachelor’s degree in data science A degree from a related discipline is sufficient. Those disciplines that qualify you for a career in data science include computer science, statistics, physics, social sciences , math, applied math, and economics.
After completing your B.Tech degree, you will need to acquire a Master’s degree in Data Science. The Masters degree is relevant as most employers prefer those with Masters degrees to those with a Bachelor degree. The proportion of specialists in the field with a master’s degree is also higher than that with a bachelor’s degree.
You can do a PhD in data science after completing your master’s degree. However, this is ideal if you are aiming for a leadership position in the field or want to teach it in a higher institution.
In summary, the minimum requirement for training as a data scientist is a four-year high school diploma in data science or a related technical discipline. To improve your chances of getting a job as a data scientist, you need to get a Masters degree in Data Science. Then you should get a Ph.D. Degree if you are aiming for a leadership position in the field.
Where can I get the best data scientist training?
Although a bachelor’s degree is the minimum requirement to get a job in data science, here we are going to discuss the masters program.
The reason for this is clear. The area of data science offers more opportunities for master’s graduates than for bachelor’s graduates.
When considering a master’s degree in data science, consider the options of accreditation, program structure, cost, financial support, and focus.
The Data Science Masters program may have Engineering and Technology Accreditation Committee (ABET) accreditation, but this is not so important. As long as the school has institutional accreditation, you’re good to go.
Best On Campus Masters Degrees In Data Science
In light of the checklist above, you can find the best Data Science Masters program here.
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 economics and social sciences, and costs $ 55,952.
New York University
The New York University Masters degree in data scientists is also commendable. The MDDS program offers concentrations in big data, math and data, natural language processing, and physics.
Carnegie Mellon University
Carnegie Mellon’s Masters Degree for Data Scientists is the Masters Degree in Computation Data Science. It’s a commendable program with an emphasis on systems, analytics, and people-centered data science. However, the program costs $ 25,750.
Columbia University
Columbia University’s Masters program for Data Scientists is one of the best programs in the US with its large number of concentrations. Some of the concentrations offered by Columbia University include computer systems for data driven science, cybersecurity, and financial and business analysis.
Best Online Masters Degrees in Data Science
The Online program in data science is no different from the one on campus.
So, you should also keep an eye out for school and program accreditation, program structure, costs, financial support, and concentration options.
With that in mind, here is the best online master’s program in data science for data scientists.
University of Notre Dame
The University of Notre Dame in Indiana, in partnership with AT&T, offers one of the best online Masters in Data Science. This online MS in Data Science is a 30-credit program.
Southern Methodist University (SMU)
Southern Methodist University (SMU) in Dallas is another place where data scientists can get a quality master’s degree in data science. SMU’s online MS in data science focuses on machine learning. Business Analytics and costs $ 57,084 for the entire program.
Worcester Polytechnic Institute
The Worcester Polytechnic Institute also offers a commendable online MS in Data Science program for data scientists. This Masters degree takes 2 years to complete its 33 credit hours and costs $ 1,566 per credit hour. So expect $ 51.678 in tuition fees.
Indiana University (IU) Bloomington
Indiana University (IU) Bloomington also offers a popular online Masters degree for data scientists. The Online MS in Data Science focuses on data analysis and visualization, intelligent systems engineering, precision health, and cybersecurity. It’s a 30 credit course that costs $ 1,498.01 per credit hour.
Regis University
Regis University in Denver, Colorado is a Roman Catholic Church affiliated university offering high quality online master’s programs in data science. His MS in Data Science seeks flexibility, if not something else. In the meantime, this 36 credit hour course costs $ 820 per credit hour or $ 29,520 for the entire program.
How much does it cost to become a data scientist?
Becoming a data scientist is pretty expensive. With salary this exciting, don’t expect the cost of education to be cheap or any data scientist would.
Depending on the level of education you need to become a data scientist, a bachelor’s degree in data science costs an average of $ 40,940 for a public college per year. These costs include tuition; Room and board; Books and supplies; Transport; and other expenses.
For private four-year colleges in the United States, you should expect an average of around $ 50,900.
For four years, you would have spent $ 163,760 on undergraduate degrees at a public university and $ 203,600 at a private university.
The Masters Degree in Data Science (online and on campus) costs between $ 25,750 and $ 55,952, based on an analysis of our best programs. An average of these numbers is $ 40.851 for the duration of the program.
Therefore, expect to spend between 204,611 and 244,451 training to become a data scientist at a public or private institution.
How do I become a data scientist?
You now know the requirements for training to become a data scientist and how much it costs. So what steps do you need to take to become a data scientist?
To become a data scientist and get a really cool salary, here’s what you should do:
Start with the preparations
You need to be sure that you want to become a data scientist first. Once you have this assurance, start building skills even before enrolling for a university degree. Start by learning programming languages used by data scientists like Python, Java, and R. Also, update your knowledge of applied math and statistics. You will find them helpful not only in college, but also for your future job.
Complete a bachelor’s degree
This is the requirement for a job as a data scientist, so it is very important. Get a bachelor’s degree in data science when you find schools that offer it. If not, get a bachelor’s degree in statistics, math, or information technology. Keep learning programming languages when you’re in college for your bachelor’s degree. Also, look for internship opportunities that can help you build a strong local network.
Get a job
With your bachelor’s degree, you can get a job. It would be an entry-level job that might not pay you as much as we planned, but that’s fine. If you have certifications in related fields, your chances of getting an entry-level job as a data analyst or scientist are better. So consider certifications in business intelligence applications, relational database management systems, and data visualization software.
Get a degree
You will grow faster in the field once you have a masters degree. Many employers are looking for data scientists with masters degrees and industry experience. As a result, in addition to getting a master’s degree, you should know how to use data management programs for companies like Hadoop, MapReduce, and Spark. Well, most Masters programs include the use of these programs in their curriculum.
Keep learning
One of the downsides to the data science career is that it is always changing. A program that you cannot do without today will be out of date tomorrow. Hence, there is a need to remain relevant in this ever-evolving area.
You can do this by taking continuing education courses that are relevant to the present day. You can also stay relevant locally by networking through bootcamps and conferences and taking part in education and training opportunities.
Tips for getting started with data science
Remember that one of the steps to becoming a data scientist is to get a job? Yes, it is crucial to find employment and gain valid work experience. However, it can be difficult to find a job, especially as a recent graduate.
To make your job search easier, here are some tips:
- Build a strong portfolio. This is very important to the success of a job in data science. To build a portfolio, you must have the appropriate experience that will add to your educational qualification. When you’ve completed projects, highlight the best and focus on the bigger ones.
- Get a mentor. A mentor is very important. This is a type of networking that you will benefit from as a mentor who has years of industry experience and can tell you exactly what companies are looking for.
- Attend conferences and meetings. If you still want to build connections that will help you get started in the industry, take part in conferences. Find and attend data science conferences. Some conferences to consider are The Shift Data Conference , KDD (Knowledge Discovery in Data Mining), and The International Machine Learning Conference (ICML). You should also consider meetups like Meetup.com , SF Data Mining, and Data Science DC .
- Use job boards. You have to search for jobs, and while meetups are likely to bring you firsthand job opportunities, you still need job boards. Look at job boards like Datenjobs, and Data Science Central .
- Pass the data science interview. The data science interview includes the following sequence: the phone screen, the takeaway task, the call to the hiring manager, the on-site interview with the hiring manager, the on-site interview – technical challenge, and the on-site interview with an executive. Prepare yourself well for each stage and see the interviews for yourself.
FAQs
How Much Do Data Scientists Make?
According to Glassdoor, data scientists make an average of $ 120.495 a year. The salary can be higher or lower depending on the company you work for. As a data scientist for Facebook, you can earn up to $ 145.365.
What degree do I need to become a data scientist?
You must have at least a bachelor’s degree in data science, computer science, statistics, physics, social sciences, math, applied math, or economics to qualify for a career in data science.
Do I need a master’s degree in data science?
Even though a masters degree isn’t the entry level level to a data science job, it is important that you get a masters degree in data science. A Masters degree improves your chances of getting a job and earning more. In addition, 70% of data scientists in this field have a master’s degree.
What’s the best way to become a data scientist?
The best way to become a data scientist consists of the following steps:
1. Plan ahead while you are still in school by learning programming languages and relevant industry programs.
2. Get a bachelor’s degree in data science or related fields such as statistics, computer science, and math.
3. Earn a master’s degree in data science by completing either an online or an on-campus program with a variety of majors.
4. Get a job and gain experience in the field.
5. Continuing education to stay relevant in the field.
How long does it take to become a data scientist?
To become a data scientist, you need a four-year bachelor’s degree and a two-year master’s degree. Depending on which degree you consider the entry level for a data science job, you need four to six years to become a data scientist.
Can I become a data scientist with no experience?
It is very rare to find data scientists with no experience, but yes, some have become data scientists with no experience. All they did was acquire the skills. So if you earn multiple certifications in this field and become an expert in using the various data visualization tools and industry programs, and have a deep understanding of programming languages, you can even get a job as a data scientist.
Can a data analyst become a data scientist?
A data analyst cannot become a data scientist simply because of years of professional experience as a data analyst or because data analysts are seen as the younger brothers of data scientists. The data analyst must acquire relevant education and skills in order for data scientists to become one.
Is data science difficult?
Data science is difficult, which is why many people fear this lucrative career. You need to learn hard skills like Python and SQL and soft skills like business and communication skills and be able to combine both to be successful in the field. However, there is more to be learned over the years as the field continues to evolve.
Conclusion
With an average annual salary of $120.495, data scientists are the best in the country. However, training to be a data scientist is just as expensive as training other careers. It costs an average of $ 204.611 for a bachelor’s and master’s degree (which is roughly the major degree you need) to become a data scientist.
Because of this, you must choose an affordable data science degree program in your process as a data scientist. We believe this post can help you find your way to a career as a reward data scientist.