Data scientist (Data scientist)
Information on this skill...
A data scientist specializes in analyzing large amounts of data, with the intention that this data can be processed in an efficient and correct way. Think, for example, of large organizations, which receive many e-mails every day. By analyzing the data (the mails) in a smart way, it is possible that the mails can be forwarded to the right department without the intervention of staff members, so that the mails can be processed faster and more effectively by the organization in question. Within ICT, this way of analyzing data is also called text mining. Text mining is a process in which smart algorithms make it possible to process large amounts of text material. For example, think of text mining of e-mails, in which certain words can be combined, so that it is most likely that the incoming mail is for a specific department. Searching documents is also much easier by applying text mining. By combining the tagging of words in texts, it is possible to process data in an effective way. Another name for data science is also called data science. In short, data science can best be described as the processing of structured and unstructured data, so that the data can be applied and used in the right way. The profession of data scientist cannot simply be seen as the profession of data analyst, because a data scientist works with predictions. A data analyst works with historical data. A data scientist tries to make valuable predictions based on big data. In other words, a data scientist will use smart algorithms to make predictions.
Data science can help organizations in many ways. Think of a customer satisfaction survey of an organization, where it is possible to test results in a fast and effective way by applying data science. In that case, the algorithm will, for example, look at the amounts of positive and negative words in comments that are posted by the customers on a webshop or via social media channels. If in a comment there are two thanks or, for example, super, this is positive. Data science therefore makes it possible for customer satisfaction surveys to be carried out faster and better. In this case, data science can be used to recognize certain patterns that can help the organization to increase customer satisfaction. For an aftersales manager, this type of information can be very important to further improve the service. Another example is analyzing the surfing behavior of website visitors to determine which action visitors are likely to perform. This kind of data is very important for a web analyst. By obtaining data, a web analyst can better estimate which adjustments need to be made in order for visitors to proceed to certain actions, such as purchasing certain services and / or goods via a website. Another name for data scientist or data analyst is also called KPI specialist.
BUSINESS INTELLIGENCE EN DATA SCIENCE
Business intelligence (BI) relates to the collection of data within the own organization, with the aim of making the organization smarter and more effective. Business intelligence therefore also relates to the collection and processing of large amounts of data, but usually only within the own organization. A major advantage of business intelligence is that it concerns known data within the organization, which makes this data very reliable in most cases. This is an important difference with data science, because the outcome does not have to be reliable in all cases. Business intelligence is focused on fixed data, in contrast to data science. Business intelligence therefore generally belongs to the work of a data analyst and not to the work of a date scientist.
WHAT DOES A DATA SCIENTIST DO:
TRAINING TO BECOME A DATA SCIENTIST
There are various suitable courses for data scientist, such as the HBO ict programme or the university study Data Science. The profession of data scientist is a profession at at least hbo level. For existing programmers, mathematicians or, for example, a statistician,various external courses are offered that can certainly be regarded as suitable courses or courses. The profession of data scientist cannot simply be compared with other professions within the ICT sector because being able to program alone is not enough. Most data scientists have a university degree. In addition, there are also plenty of external training institutes where you can follow a course. Accounting isalso important as an independent entrepreneur.
COMPANIES WHERE A DATA SCIENTIST CAN WORK
A data scientist generally works for larger companies, institutions and governments that deal with big data. Think, for example, of banks, pension funds, insurers, retailers and IT companies. As described earlier, a data scientist can also work for the government, because the government also has to deal with big data. Think, for example, of a data scientist who works for a ministry or a data scientist who works for Rijkswaterstaat. A data scientist can therefore in some cases also be regarded as a civil servant. In addition, a data scientist can work as an entrepreneuror as a consultant.
COMPETENCES DATA SCIENTIST
One of the most important competencies of a data scientist is that he or she has knowledge of statistics. Mathematical insight can also be regarded as an important competence. Because a data scientist in most cases has to deal with various other specialists, such as economists and managers, communication can be regarded as an important competence. Generally important words are analysis, perseverance, cooperation, open-mindedness, accuracy, innovativeness and conceptual thinking. Finally, it is not unimportant that a data scientist can program and has extensive ICT knowledge.
LABOUR MARKET PERSPECTIVE AND CAREER OPPORTUNITIES AS A DATA SCIENTIST
The labour market perspective of a data scientist is very good, if you have the right studies. Big data is important for many companies, institutions and governments, so getting work as a data scientist is generally not a problem. More and more organizations are dealing with big data, which cannot simply be processed by ordinary database management systems. The need to analyse data at an early stage is also increasingly important for organisations in general. The career opportunities of a data scientist cannot simply be indicated, because the career opportunities can differ per employer. A possible follow-up function is the profession of market researcher.
TERMS OF EMPLOYMENT AND SALARY DATA SCIENTIST
There are no specific examples of the employment conditions as a data scientist because you can work for various types of companies, organizations and governments in different industries. A data scientist employed will typically earn a salary between 3500 and 4500 gross per month depending on age, education and further responsibilities.
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