Data scientists don’t simply analyse data. They use that information to progress medicine, transport and even predict the future.
Data science is still one of the hottest sectors to get into, and there’s so much more to it than simply mining huge amounts of data.
Data is at the centre of everything, which is why data scientists are so important in all aspects of life. We’ve previously talked about what you can do as a data scientist, how much you can earn and what kind of skills you might need.
However, not many people understand the real-life implications of what it means to be a data scientist, or the kind of practical work that these people do.
So, we’ve rounded up five surprising, cool areas that data scientists can get into, to use their powers of data mining and analytics to really make a difference, be it for everyday enjoyment or for life-saving technologies.
In medicine
When it comes to fatal diseases such as cancer, early detection can be the key to saving hundreds of lives.
Recently, 10,000 data scientists took part in a Data Science Bowl, a competition designed to tackle real-world problems using data science.
The participants competed to develop the most effective algorithm to help medical professionals detect lung cancer earlier and with better accuracy.
The winning algorithms, along with a number of other high-ranking ones, will be examined by the US National Institutes of Health, and the Food and Drug Administration, to see how these algorithms can be applied in software that reads scans.
In finance
Data is already used to detect and prevent insurance fraud, but it requires a human element in order to make it as accurate as possible.
Fraud detection units without a data scientist at the helm can often have a blanket approach to claimants, giving innocent parties a tougher time and a bad customer experience.
No matter how automated the system gets, claims that are flagged as fraudulent need to be reviewed by a human; not to mention the fact that humans need to produce the algorithms that make the automated systems smarter.
It’s not just the insurance industry that needs data scientists. Financial institutes are increasingly finding the need for these skilled individuals when it comes to loans and accurate credit scoring. After all, our banks have so much of our data at their fingertips just waiting to be properly mined and analysed.
In transport
Driverless cars could produce as much as 1GB of data per second. This data is and will be used to make self-driving cars safer and more reliable.
There are a lot of issues around the autonomous car world, so the more involved data scientists are, the better.
AI is getting closer to behaving like a human brain every day, with continuous data input and humans teaching computers how and what to learn.
Data scientists will be an essential part of putting automatic vehicles on the road safely.
In gaming
What? You didn’t know that data science was an essential part of creating video games? In fact, they work with a significant part of game production as well as combing through essential post-game analytics.
With so many gamers playing online, the amount of data that gaming companies can glean with very little effort is astounding. This means that they need data scientists to analyse this information and use it to produce better games and make improvements to current ones.
Data scientists can also use data to find out when players give up because certain levels are too difficult or too easy, providing a better overall gaming experience.
Additionally, they can create algorithms for game enemies to analyse your movements in motion capture games and react accordingly.
In general
From accurate weather predictions to the next big music hit, data scientists are becoming the closest thing to psychics that this world is likely to see.
Insights into customer behaviour, along with data about music, can help data scientists to ascertain what the world needs next from the music industry.
Data scientists are also naturally involved in making more accurate weather and storm predictions, both on a short and long-term basis.
Basically, data scientists can predict the future. What’s cooler than that?
