For a long time, companies of all sizes have gathered customer data and analyzed it to offer better services and improve sales. Data cannot help us as it is. It needs to be processed using software and other non-traditional methods.
Professionals who specialize in the interpretation and analyzing data are called data scientists. Their skills are needed to help improve operations. Some data scientists have backgrounds in related areas, but you can start out without any knowledge. This knowledge helps analyze large data sets and identify patterns or trends. In addition, a data scientist can develop new ways of storing and collecting data.
How to start
Analytical and mathematical skills are a good foundation for data science. In addition, a data scientist must understand how to handle statistical software packages and know some programming languages. Therefore, it is also essential to have certification from a recognized program.
Pre-experience and prerequisites
You need a strong computer science and mathematics background. Experience handling large data amounts is also an added advantage. You may also benefit from the machine learning experience and statistical modeling.
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We cannot have one specific way of becoming a data scientist. However, some prerequisites and experiences may improve the chances of you doing well in that field. They include the following:
- A computer science and mathematics background: the job demands handling large data sets daily. A strong foundation in computer science and mathematics is needed. In addition, you should be conversant with statistical algorithms and methods.
- Capability to handle large data amounts: it is important for a data scientist to analyze and manipulate large data sets. He or she needs experience with data sets before entering the actual field.
- Experience in statistical modeling and machine learning: these two are very powerful, and every data scientist needs them to make predictions. With some experience and techniques, you will be better positioned to thrive as a data scientist.
- Good communication skills: a data scientist has to communicate all their findings to stakeholders and other interested parties. As such, you need string visualization and communication skills. In addition, data presentation should be easy to tackle as it makes explaining much easier.
- Learning drive: data science is an ever-evolving field. Learning never stops, even after you land a job. There is always some new techniques or methods to catch up. Therefore, being ready to learn constantly throughout your career is essential. You can join boot camps and other educational program to qualify. However, you will still need to refresh your skills occasionally.
Becoming a data scientist
This is a study area that has to do with the extraction of knowledge from raw data that has been gathered. This profession is in great demand currently, especially for people who can analyze and offer the most competitive advantage to companies and businesses. Such a career helps you create business analytics and solutions that are driven by data.
Getting a bachelor’s degree is one of the best ways of getting started in data science. You can choose a field associated with data science like:
- computer science
- statistics
- data science.
Some companies will check for a bachelor’s degree when hiring.
- Learn relevant programming languages: getting a bachelor’s degree is good, but you should appreciate that it only gives your theoretical understanding. You need to brush up on some relevant programming languages needed in data science. You can include SAS, SQL, R, and Python. These languages are essential when you are handling large sets of data.
- Get to learn other related skills: after learning the programming languages, you need to familiarize yourself with other tools needed for big data, machine learning, and data visualization. For example, you must know how large data sets should be handled, cleaned, sorted, and analyzed.
- Get certified: getting skill and tool-specific certifications is an excellent way of showing you have expertise and knowledge in a certain area. Some certifications can help you along the way, including Tableau course and Power BI certifications. Consider how the tools you pick will help you as a data scientist, and find out what other established data scientists use.
- Internships: you can boost your career through internships in good companies. You need jobs that include things like data engineering, statistician, business intelligence analysis, or data analyst. Getting such an internship offers you hands on experience with the job and everything it entails.
- Entry-level jobs in data science: when you are done with the internship, you may get a job offer from the company you were working for if they are impressed with your work and are hiring. If not, you can still look for a job at an entry-level position. This is the only way to gain more experience in the field and start the climb up in your career. In addition, you can expand your skills and knowledge with an entry job.
Data science example
Being a data scientist offers the chance to work in almost all industries, although you may have a preference. One of the best examples of data s science at work is the media provider Netflix. This is one of the places where you can understand how exactly data science works. Netflix offers a personalized experience because it measures the retention and engagement of users. This includes:
- The time and day of the week you get to watch content on the channel
- When you fast forward, rewind, or pause
- What and when you leave content
- Your location in the world
- Your scrolling or browsing behavior
- Your device
Netflix has more than 120 million users worldwide. This is a lot of information to process accurately. Therefore, Netflix has to utilize data science metrics for things to work. Looking at the viewer behavior also guides Netflix on the shows to create.
Netflix is a good example of the way data science works. The skills you gain as a data scientist can take you to any industry you choose. Data science has great potential and we can expect some good things here. A career in this field is a wise decision.
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