I get this question a lot when I tell people I’m a data scientist. The truth is there is more & more upcoming data scientist in the industry. Take a look at the growth in trend for the search term ‘data scientist’ through the years.
Growing trend of term ‘data scientist’ taken from Google Trends
In this post, I’d like to clear the doubts & questions you may have about data scientists and what they really do.
What Is Data Science
Before I dive into what a data scientist do, you should know what data science is.
Data science is a field increasing sought after by corporates and enterprises. In simple words, it refers to the processes, systems and methods used to analyze large amounts of data. Actionable insights are then derived at the end, used by corporates, enterprises and organizations to gain a competitive edge.
So What Is A Data Scientist & What They Really Do?
Some people refer data scientists as ‘modern’ business analyst. That isn’t exactly incorrect as the training we data scientists & data analysts undergo are quite similar. Some of the training that I’ve gone through to be a data scientist, includes computer science studies, modeling, statistics, maths, and analytics.
So what makes a data scientist different? Being a data scientist is all about asking questions, making new discoveries and learning new things. We do this by analyzing large sum of data, creatively thinking of solutions and give businesses a competitive edge. Whereas a traditional data or business analyst who only look at data from a single source, data scientists analyze and explore data from multiple difference sources, from sales data, CRM machines, online analytics, social networks and even physical sensors, to name a few.
A good data scientist is someone who a large skill set, ranging from analytical skills, programming, coding, machine learning, data mining to business skills such as business acumen and communication skills. However, the skill that takes a data scientist from good to great is the skill of being able to explain conclusions derived from data that can be easily understood by non-technical people.
Put simply, a data scientist is someone who knows how to interpret data and extract useful information from it by finding patterns, building models and running experiments.
First, a data scientist needs ask an interesting question. What is the goal of carrying out analytics and which data is needed? Second, a data scientist will build a system to collect data. Not all data is structured. Some data is unstructured, so the challenge of being able to mine both structured and unstructured data. Next, collected data is explored to find any patterns or abnormalities. After that, a data scientist then models the data by building models and validating it. Finally, the finding and studies from analyzing the data are visualized. The conclusions will be communicated to the organization or business. With a clear a visualization and communication about the findings from the data, insights which are previously hidden can show a lying business issue or give a competitive advantage to an enterprise or organization.
The Skills Needed To Be A Data Scientist
So what are the skills that one would need to call himself or herself a data scientist? I mentioned in my earlier blog post that I didn’t become a data scientist by choice. The skills I pick up along the way eventually made me a data scientist.
There are lots of skills that you’ll need to be a certified data scientist. But to keep things simple, here are four skill areas that you absolutely must master to be a good data scientist.
Programming
A data scientist will need strong programming skills
If you’re going to work with technology, you’ll need to learn how to program. It’s your everyday work. Because you’ll be working with data, you’ll find working on activities like sampling, processing and tackle certain data problems.
All these steps require computer programming. Some programming languages that I recommend you to learn are Python, Node.Js, Ruby, Java, Javascript and C#.
People with computer science background will have the advantage in this area. Don’t worry if you don’t have a computer science certification, it’s possible to learn programming no matter your level of understanding.
Strong Quantitative Skills
Being able to analyze and interpret data is what makes a data scientist.
A good data scientist needs great mathematics, statistics, and analytical skills. Collecting, validating, and interpreting data is the everyday work of a data scientist.
Without strong quantitative skills, collected data can be misinterpreted and a whole data science project can go horribly wrong. Basically, you’ll need to have the skill to create reasoning using numbers & data.
A Good Business Understanding
It all comes down to making good business decisions with the help of data.
Even if you know how to mine & analyze data, it all does not mean a thing if you didn’t understand the business problem at hand. As I mentioned earlier, every data science project starts with identifying a business problem.
I’ve seen many data science & big data projects failed because of the lack of business understanding. You will need to know what business problems you’re trying to solve and think of ways a business can gain a competitive edge by harnessing data.
Visualization & Communication Skills
Without great communication, people won’t be able to understand your data research.
To be a good data scientist also means you’ll have to be a good communicator and visualizer. You might have great technical and quantitative skills to get the job done when mining and studying data, however, for your findings and analytical models to become useful for a business, you’ll need to be able to communicate information to business people.
For instance, a sales & marketing team might not be able to understand technical terms. In fact, there is a high demand in companies looking for good data scientists with great communication skills who knows how to communicate data findings with non-technical teams within their company.
Without getting too technically complex, a data scientist must be able to visualize his or her reports & statistics in user-friendly ways and communicate the information in layman terms that people can understand.
Conclusion
I hope you got a good idea on what a data scientist really do and how they continue to impact businesses. Data science jobs are growing in demand as more and more businesses are embracing the importance of data, the ability to analyze it and use it as a competitive edge.
Also, did you know being a data scientist is rated as the best job in America by Glassdoor? If you’re wondering about the data science salary, you’ll be happy to find out that data scientists are paid quite well.
So it’s your turn now. It’s never a better time to learn data science than now. As complicated it might seem to be, even non-technical people will have a lot to gain from understanding data science.
Get started on data science and get the competitive edge for your business now. Email me on drlau@www.drhanlau.com or simply comment below as I’ll love to hear from you.