Entrepreneurial Data Scientist Kevin Jolly is all too aware of the many opportunities that lie ahead as our relentless ability to produce ever increasing amounts of data shows no sign of abating. Durtti wants Kevin to share how he is helping children, adults and businesses to prepare for the impending Data Revolution.
Can you briefly describe the purpose of your business, LinearData, Kevin?
LinearData aims at being a media outlet that’s hyper focused into the world of Data Science and Artificial Intelligence.
We provide comprehensive guides with in-built reproducible code that people can use to make their own data science projects from scratch.
In addition, we also provide industry relevant news and updates.
What was the most valuable lesson you learnt as a summer intern at 3M?
Working for an organization as large as 3M taught me that managing your time effectively to meet targets is vital for success.
It also showed me that communication is key, and building meaningful relationships with your clients is vital in order to collect the right data that can help your client solve his or her problems.
If you were given one hour to get a class of primary school children curious and excited about a career in data science, how would you go about it?
Explaining how data can build a better and smarter planet that would help the people around them lead more beautiful and technologically advanced lives is how I would go about this.
On their level, going deep into the technologies behind data science won’t help, but what I believe would get them curious is what they can do with the data that the world generates in large amounts.
In this regard, I would talk about how they can build systems that can think for themselves, and how data is the fuel that powers these machines.
With the benefit of your experience, what do you believe we will be able to achieve by analysing data in 5 years time that we can’t achieve today?
The major difference in 5 years will be the volume of data that is generated.
This will impact the kind of systems that we can build in the future.
Like I said, data is the ‘fuel’ that powers smarter systems.
More data equates to more machines that utilize the power of Artificial Intelligence.
I believe that in this timeframe, most homes will have at least one device that is powered through this data.
You have written many comprehensive guides on both Data Science and on other AI related topics. Is there a common goal you wish to achieve that is true for all of the guides you write and if so, what is it?
My goal is to make Data Science simple.
Many people believe that in order to be a good data scientist one has to be an expert programmer.
Although this is true to an extent, programming does not have to be hard.
I want people to remember that Data Science in bulk is mostly dependent on mathematics and statistics, and programming is merely the tool that we use to extract meaningful insights from this data.
My guides provide users with code that they can simply copy and paste from my website into their own projects with a few minor modifications that they can implement on their own.
The guides provide users with a step by step procedure that they can follow irrespective of what background they come from.
We aim at teaching Data Science to 10 year olds all the way to industry veterans who are hoping to make a career change into the world of data.
How well prepared do you believe most businesses are today for the seismic changes (and opportunities) that lie ahead within Data Science in the next 5 years?
During 2016-2017, businesses around the world have invested 3 times more into their data and AI functionalities compared to the previous year.
This is an optimistic increase in the spending for data centric businesses.
The tech giants like Google with DeepMind, IBM with Watson, Amazon and Facebook show us that data and AI will pave the way into a future where data will govern how we do business.
What are the most fundamental things that a business needs to do, or changes it needs to make, in order to be better prepared for the near future in your opinion?
McKinsey predicts that by the year 2020 we would required over 2.8 million professionals that are skilled in Data in the USA alone.
This shows us that businesses who are not prepared for the data revolution will be left behind.
If data is the new oil, mining this data is the way forward if a business wants to stay relevant.
In this regard, training programs within the company will become vital for a business.
Hiring fresh graduates from universities who are passionate about the field and training them in data is also another option that they can consider.
Finally, Kevin, what 3 key qualities do you believe an aspiring Data Scientist needs to possess, and why, in order to build and maintain a very successful career in the next 5-10 years?
In my opinion the first quality that a person would require is a passion for getting excited whenever they uncover an insight from large volumes of messy data.
Second would be a passion for solving problems on an every day basis.
The third, and most important quality, would be the ability to learn fast and learn well.
In the field of data technologies, things will keep changing every 3-5 years and new and better technologies will take over from older ones.
The programming language that you learn today will become obsolete in a couple of years.
So it is very, very important that you have a passion for learning new things – all the time!
Kevin is a member of The Artificial Intelligence Group on LinkedIn.