Did you know that data science was named the hottest job of 2018, according to job search and company review site Glassdoor?
With this growing demand for skilled data scientists in Singapore, you might be wondering what it takes for one to become a data scientist.
Aside from technical skills such as Python, R, and SQL among others, should you also be data-driven in your private life? Or perhaps possess logical thinking skills?
We spoke to Kit, Tech and Data recruitment consultant at Principle Partners, to find out what recruiters look out for these days when hiring data scientists.
Here are three qualities you need to have to become a data scientist:
“Curiosity killed the cat” is a proverb often used to describe the consequences of probing into matters that are not your own. However, this warning does not seem to apply to the field of data science.
Data science is a field that is constantly evolving. New research and technologies are being discovered everyday. Processes can always be improved to generate better results.
A data scientist must be able to keep up with the constant changes in this field. Having “an open mind combined with a willingness to learn and improve should set you ahead of the pack in the years to come”, Kit added.
In the field of data science, it might be useful to remember the rejoinder used to counter the proverb—”Curiosity killed the cat, but satisfaction brought it back.”
In essence, be curious. Don’t be afraid to ask questions. You will be rewarded for it.
Data scientists don’t just wrangle data—they must be able to use said data to solve business problems. That is what sets a regular data scientist apart from an exceptional one.
This means that if you want to be a proper data scientist, you need to have a strong understanding of the industry that you are working in. After all, a business problem can’t be solved without proper understanding of how the business operates, right?
Kit, who specialises in recruiting Data Science and Technology candidates, remarked, “It’s awesome when a data scientist knows that real value comes from delivering the results that truly matches the actual business need. Impact!”
Beyond identifying critical problems to solve for your company, a great data scientist should also recognise new ways that the business can leverage its data.
Besides analysing data, data scientists must also be able to clearly articulate their findings in non-technical terms to the rest of the team.
Stakeholders are more likely to be interested in how such data can add value to the business, hence it is important for the data science team to translate such findings into solutions.
Kit shared, “If you’re having trouble finding the right words, it may be good to practice presenting and communicating with your peers, or even attend classes and events where you can share your ideas. Practice makes perfect.”
If you want to be a great data scientist, having the technical skills is, of course, crucial. But don’t forget the other components we have mentioned in this article that will definitely give you an edge over your peers!
Want to take your first step into data science? Sign up for UpCode Academy’s Introduction to Data Science course now!
(Featured image: Principle Partners)