Surely in recent months, you have heard about how companies give more and more value to data and, related to it. The professional profile of a Data Scientist. And it is not strange that you have heard the name of this position since it is one of the professions whose demand has grown the most in the last year in Spain and one of the best paid today.

However, are you clear about what a data scientist does and their role in a company? In this article, we explain simply what a Data Scientist is. Its functions, and what skills and knowledge you must develop if you want to become one. Let’s go there!

What you are going to see in this post

  • What is a Data Scientist, and what is their role within an organization?
  • Functions of a Data Scientist
  • What does it take to be Data Scientist?
  • Higher technical qualification
  • flanguages a data scientist should know
  • Know-how, platforms and technologies
  • Skills of a Data Scientist
  • Experience working with data
  • How to train in Data Science?
  • Undergraduate and postgraduate degrees in Data Science
  • Courses to become a data scientist
  • Certifications in Data Science
  • How much does a data scientist earn?
  • Conclusion: Why learn data science?

What is a Data Scientist, and What is Their Role Within an Organization?

A Data Scientist is a professional dedicated to collecting, analyzing and interpreting large volumes of data to extract the relevant information from them. They are people who apply their knowledge in mathematics, statistics and programming to analyze and interpret the data available to companies and extract valuable information from them.

Organizations have a large amount of information at their disposal, which is well used to translate into a benefit for the company. In a progressively digital and competitive environment, it is almost an obligation to take advantage of the information companies obtain relating to their environment. Hence the growing need for professionals capable of analyzing and making sense of all this data so that it supposes an actual value.

Thanks to the work of data scientists, companies can predict user behavior or discover new business opportunities. For example. They may know the best time for a customer to purchase a product, which of all the available options best suits their preferences, or the risk of that person getting sick.

The role of Data Science within an organization is to provide valuable information about the behavior of consumers and the actions that the company carries out so that it can design strategies and business plans that drive it to meet its objectives.

New technologies have multiplied the amount of information available in recent years, and its processing has become possible thanks to the emergence and evolution of disciplines such as Machine Learning. This. Together with the advance in digitalization, has meant that companies are betting on taking advantage of the potential of data and, consequently, that professions such as data scientists are booming.

Functions of a Data Scientist

What a Data Scientist do in a company? The roles of a data scientist may differ from organization to organization but broadly include the following:

  • Data extraction. Acquire all the information you consider help from various sources. The volume of data may differ (Small Data, Medium Data and Big Data).
  • Data cleansing. Delete all information that is not relevant and prepare the data for processing (normalizing values, modifying variables, etc.).
  • Data processing. Treat the data by applying statistical approaches, analytical software, Machine Learning, predictive models, etc., to obtain valuable information.
  • Data visualization. Represent data in a variety of ways to make it understandable.

What Does it Take to be a Data Scientist?

To work as a data scientist, companies demand to have a series of technical knowledge and skills. Let’s see in detail what they are:

Infographic on what technical knowledge and skills are needed to work as a data scientist.

Higher Technical Qualification

Data Scientist job offers usually include a first requirement to have a higher technical degree.

A technical degree such as Computer Engineering or Telecommunications is usually requested to work as a data scientist. But there is also a frequent demand for degrees in analytical disciplines, such as Mathematics or Statistics. Or in the business field, such as Economics or Business Management. In short, we are looking for people with knowledge in programming, analytical skills and business understanding.

However, a higher degree is not a determining factor currently in the market when hiring a Data Scientist. It is widespread to see data scientists from other fields, such as physics or social sciences (psychology or sociology, usually). Of course, they are usually people familiar with data analysis.

Programming Languages a Data Scientist Should Know

There are numerous programming languages to practice data science (Scala, Pearl, Julia…). However, three are the most popular and the most frequently demanded in job offers: SQL, Python and R. But a Data Scientist doesn’t need to be an expert in all three. Typically, you are asked to handle SQL and work with Python or R.

  • Structured query language (translated into Spanish) is essential for manipulating structured data. It is a domain-specific language designed to modify. Locate, and verify information from relational database management systems. Allows you to perform queries to retrieve data from databases and make changes.
  • It is the programming language most commonly used by data scientists. It is a general-purpose, object-oriented language with a readable syntax. Which allows you to implement Machine Learning on a large scale. All kinds of work related to data science can be done through its libraries, such as Pandas. Python is more replicable than R, so it’s the best choice if you need to use the analysis results in an app or website. It is usually the option that developers or professionals who already know programming opt for. We could use Python, for example, to develop a machine learning application.
  • It is a language used to perform statistical analysis and has, therefore, a more specific use. This is the preferred choice for statisticians and academics. It has an infinite number of packages to perform any action related to data analysis. One of its strengths is that it dramatically facilitates information visualization, allowing to generate reports and presentations only. We could use R, for example, to analyze customer behavior.

Python and R are two languages widely used in Data Science, with which we can do practically the same. Although each of them seems to have a different approach.

Know-how, Platforms and Technologies

In addition to the technical and analytical skills that the professional has developed during his higher education and working with the programming languages that we have just mentioned. A Data Scientist must have additional knowledge and control of a series of tools and platforms to carry out his work.

Specifically, it is usually requestee that you have an understanding and theoretical/practical mastery of Mechanism Learning and Deep Learning procedures and the management of SQL databases. It is often also valued to know about NoSQL databases. This is usually accompanied by understanding statistical research techniques, such as modelling, clustering, data visualization, predictive analysis, etc. Instead, a data scientist may need to work with Big Data environments such as Hadoop or Spark, among others.

Each job may require some technical knowledge or others, which depend on the company’s needs that offers it. However, these are the ones that are usually asked to work as data scientists in a generalize way.

Skills of a Data Scientist

In addition to this technical knowledge, a data scientist must develop some skills. The most frequent are:

  • Problem-solving ability
  • Continuous learning
  • Effective communication
  • Business Vision

All of them are essential for Data scientists to carry out their work successfully.

Experience Working with Data

Finally, the experience require to work as a Data Scientist varies depending on whether the job offer is aimed at more junior or senior profiles. For more inexperienced profiles. Companies usually ask for 1 or 2 years of experience working with data. Whereas, in more experienced positions, at least 4 or 5 years of experience working as a data scientist are require.

How to Train in Data Science?

Currently, there are many training options to become a data scientist. We find countless university and postgraduate degrees, courses and certifications. Let’s review them:

Undergraduate and Doctoral Degrees in Data Science

Numerous Spanish universities offer degrees to train you in data science. Some of the best-known programs are the Degree in Applies Data Science of the Open University of Catalonia. The Degree in Data Science and Engineering from UC3M; the Degree in Data Science and Artificial Intellect from the Poly University of Madrid; and the Grade in Mathematical Engineering in Data Science of the Universität Pompeu Fabra.

There are also double degrees dedicate to developing the skills necessary to work as a Data Scientist. One of them is the Double Degree in Computer Science and Mathematics offered at universities such as the Autonomous University of Madrid, the University of Barcelona and the Polytechnic University of Valencia.

For its part, the world of postgraduate and master’s degrees specialized in data science is very wide in Spain. Both public universities and private centers offer many programs. To mention a few. The Completeness University of Madrid, the Universitat Autònoma de Barcelona and the University of Navarra have specialized higher programs in Data Science. Numerous business schools also do so, such as EAE, ESIC or IBS.

Courses to become a Data Scientist

In addition to the universities’ degrees and master’s degrees, there are many online courses to learn data science. Thus, platforms such as edX and Coursera have numerous resources to train you extensively in the discipline or in some of the languages of media that you will need to know to work as a data scientist.

Some of them are IBM’s Introduction to Data Science, Machine Learning for Data Science and Analytics at Columbia University; Python basics for IBM Data Science. And Data Science: R Basics from Harvard University. In MiriadaX, we also find the course Introduction to Business Intelligence and Big Data at the Open University of Catalonia.

Certifications in Data Science

Alternately, there are also many certifications to accredit your knowledge in Data Science. Some of the best known are Saas Data Science Certification, Microsoft Azure Data Scientist Associate, IBM Data Science, or Google Data Analytics Certificate from Google. Some are available on Coursera.

How Much Does a Data Scientist Earn?

Another issue that usually comes up when we talk about the work of data scientists is how much they charge. A Data Researcher has a minimum salary of € 34,000 gross per year in Spain in 2021. This is the figure provided by Glassdoor. A platform in which professionals share their salaries anonymously after analyzing the salaries of half a thousand scientists.

If we go to job portals such as indeed or jolted, the figure does not change too much. The first speaks of € 32,660 gross per year and highlights Madrid. Bilbao, Valencia and Seville as the Spanish cities where the salaries of data scientists are higher.

For its part, the second portal opts for the amount of € 38,700 (around € 2,100 net per month) and contemplates an annual bonus of € 6,540. The job also points out pretty notable salary differences between the most inexperienced and the most experienced professionals. In this way, a Junior Data Scientist would charge on average € 29,400 gross per year and a Senior Data Scientist € 54,600.

Conclusion: Why Learn Data Science?

As we have seen, Data Scientist is one of the most demanded professions today and with better salaries in Spain. With the acceleration of digitalization and the growing interest of companies in data, it does not seem that the trend will change. Data scientists will continue to be a much-needed profile in companies for years to come.

Therefore, in this article, we have tried to dissect the profile of a data scientist. We have seen what a Data Scientist is, what he does in his day to day, what technical knowledge and skills he must develop and what training resources exist today to become one.

Review Data Scientist: What Needs to know?.

Your email address will not be published.