A data scientist is someone who can solve complex data problems. So, as you can imagine, a data scientist needs to have strong expertise in different fields that can include computer science, statistics, and mathematics, among others.

In addition to this, a data scientist uses the latest technologies to find the best solutions and conclusions for a company's growth.

Ultimately, a data scientist takes raw data and transforms it or looks at it from so many different perspectives that he can withdraw valid conclusions. Besides, some of these conclusions may be used to make decisions.

What Does A Data Scientist Do

One of the most important things to keep in mind is that a data scientist can work in many different industries. After all, data science has many different uses between creating new products, innovating in their sectors, and even making the world more efficient. But let's take a look at some practical examples so that you can understand what exactly a data scientist does.

1: Logistics:

UPS is just one of the many logistics companies that decided to use data analysts to save money and improve their overall revenues. Putting it simply, the company is used data science-backed statistical modeling and algorithms to build the On-road Integrated Optimization and Navigation (ORION) tool. This tool allows them to create the best routes for delivery drivers and it takes into consideration a wide range of factors such as construction, traffic, and weather, among many others.

By using data science, the company is saving a lot of money not only in fuel but it is also prolonging the life of their trucks since they don't need to do so many miles.

2: Healthcare:

The healthcare industry is a perfect example where you can see a wide range of areas and tools that are using data science. Since healthcare companies have been collecting data for many years now, they are now using it to diagnose diseases faster, practice preventive medicine, exploring new treatment options, and even understand diseases.

3: Finance:

Both data science and machine learning have been being used n the financial industry for quite some time. The reality is that they already saved this industry not only time but millions of dollars as well.

Some fintech companies like PayPal and Stripe have been investing a lot of money in data science so they can be more efficient in detecting and preventing fraudulent activities. Another example is JP Morgan’s Contract Intelligence (COiN) platform. Simply put, this platform uses NLP (Natural Language Processing) to process and extract vital data from around 12,000 commercial credit agreements each year. To see the huge gain this represents, this would take about 360,000 manual labor hours to complete when it is now being done in just a few hours.

4: Self-Driving Cars:

Companies like Google, Volkswagen, or Tesla are making huge investments in data science to ensure their self-driven cars are safe. These companies are all using predictive analysis.

They have all their prototypes filled with thousands of tiny and micro sensors and cameras to get information in real-time. Then, by using machine learning, predictive analytics, and data science, self-driven cars "know" how to avoid dangerous lane changes, can adjust to speed limits, and they can even take passengers on the quickest route.

5: Cybersecurity:

There's no question that if there is an industry that has been increasing its importance is cybersecurity. After all, we spend more and more time online making us more prone to identity theft, for example.

Kaspersky, an international cybersecurity company, is already using data science as well as machine learning to detect malware, for example.

6: Entertainment:

Well, data science is present even in the entertainment industry.

If you like to listen to music while you are working or simply when you are relaxing and you use Spotify, then you may have noticed that it recommends the perfect songs for you. Well, this isn't a mistake as well as it isn't luck. Spotify is already using data science to better serve its customers like you. But Spotify is not alone. Netflix is another entertainment company that is also using data science. Simply put, the company uses a data aggregator that recognizes the type of shows you like and recommend the most pertinent ones.