In the past few years, machine learning, artificial intelligence, and ultimately data science rose as _the _buzzword of the industry.
Of course, there is a reason for this phenomenon. New algorithms and new hardware made complex prediction systems affordable for many companies. It’s not hard to find a use case in the industry about how they overcame a massive problem using a thousand-layers convolutional neural network. And really, this is a good thing.
Who never wanted a crystal ball?
Nevertheless, machine learning and artificial intelligence have been topics of research in academia for decades. They are not new. Now, they are just more accessible. Almost anyone can run a python notebook, import scikit-learn, load a pandas data frame and… fit it.
🎶 Just fit it, fit it, fit it, fit it,
No one wants to be defeated 🎵
Yep. No one wants to be defeated in the market. And the Internet is full of tutorials about how to train your ̶d̶r̶a̶g̶o̶n̶ model. And you just have to be careful about the overfit monster. Right?
No.
Don’t take me wrong. There is plenty of valuable content on the Web, and it’s important to learn. However, based on my experience, if you want to be a successful data scientist, you need to go beyond the machine learning recipes. Here are three high-level skills I believe all Data Scientists need to master (or develop):
- The scientific method
- How to create value for the business
- How to communicate findings appropriately.
On the one hand, data scientists with a solid academic background are usually good at the scientific method. However, they often get too excited delving into interesting research and may forget about what the business really needs. On the other hand, data scientists that grow in the industry tend to neglect the rigour of the scientific method.
The third skill is really something apart. I strongly believe it depends on the experience of the individual, and it may even be associated with his or her personality.
The good news is: even if you lack one of these skills, you can learn them and develop yourself.
#data-science #business #scientific-method #machine-learning #communication
