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Data Scientist looks for connections and patterns in the data sets that will allow them to create a model that predicts the result before an event actually happens. ML experts and data scientists use mathematical statistics to analyze the data and get some valuable insights from it.
In this post, we will discuss where data scientists can apply their knowledge and whether this profession is truly useful and in-demand.
What is Data Science?
Data Science works with Big Data. Big data is a huge amount of unstructured information: for example, meteorological data for a certain period, statistics of queries in search engines, sports results, databases of microorganisms genomes, and much more. To work with such data, scientists use mathematical statistics and machine learning methods to make predictions. What kind of predictions depends on what problem needs to be solved. The result of the data scientist’s work is a predictive model. To simplify, this is a software algorithm that finds the optimal solution to the problem. A good explanation of the difference between machine learning and data science, you can find on this page.
Is it really useful?
A lot of services that we have already use the discoveries made by data scientists. And you see the results of their work every day. For example, these results are used by chatbots, voice assistants, recommender systems, and so on. The list of possible friends on social networks such as Facebook is also the result of Data Science. Search engines and face recognition programs are also based on algorithms written by data scientists.
Where do Data Scientists usually work?
Here are some options:
- In business – in any industry. For example, a data scientist creates algorithms that predict the demand for a company’s services. Other algorithms will help decide if a company needs to open a new line of business.
- Banks. Data scientists write algorithms that analyze large volumes of data to prevent fraud and increase security.
- In transport companies. For example, AI programs made with the help of data scientists help to build the best routes.
- In IT. A data scientist develops bots, search algorithms, and artificial intelligence systems.
- In production. For example, programs predict equipment failures and product defects.
- Insurance companies. Machine algorithms estimate the probability of an insured event.
- Medicine. More and more devices automatically diagnose based on objective data. For example, the program can indicate damaged organs on X-rays.
- In agriculture. The algorithms give a forecast for the harvest and select the optimal land-use systems.
- Bioinformatics and modern genetic research are unthinkable without Data Science. The programs build genetic maps and determine the types of organisms.
This is not a complete list. Wherever predictions are needed, deals are made, or risks are assessed, Data Science comes in handy. Therefore, if you decide to follow this career path, you will always have plenty of interesting tasks to work on.
