Recently, David was gracious enough to briefly talk to me about his experience as a Data Scientist. It was really interesting to learn more about Data Science and hear about the different ways it can impact and influence how organizations make data-driven decisions. In addition to being an accomplished ‘data nerd’, David has also completed 4 Ironman triathlons (say what?!), is married to his wife Sarah, and has 2 kids- Carolyn and Luke.
1. What exactly does a Data Scientist do?
To put it simply, a Data Scientist’s job is to uncover actionable insight by analyzing data. A Data Scientist performs tests on data to find patterns, build models and algorithms where the results are visualized so others can understand and take action against them. Evidence of Data Science is all around us- from movie recommendations on Netflix to sales forecasts and predictions on retail products.
2. What is the most challenging aspect of being a data scientist?
When Data Science is done well, the results make the process look easy. But what you don’t see are the countless experiments that didn’t work, and of course the ‘gremlins’ or data anomalies that pop up in the data. But most people don’t talk about these things because they aren’t sexy, even though they are an everyday part of data science.
3. In your opinion, what is one trend in data science you think will have a significant impact in the near future on organizations?
In my opinion, the press has really overhyped Deep Learning but it’s potential business applications are huge. Organizations that are able to effectively apply Deep Learning to their business problems will have a real competitive advantage.
4. What has been most rewarding about the projects you work on at Precocity?
When I’m able to quickly turn urgent client requests or tasks into truly actionable insight, there’s no better feeling. In Data Science, it’s easy to fall into the ‘analysis paralysis’ trap, because there’s always another way to make your results more precise, but businesses need data to move quickly and make quick decisions and I truly enjoy being a big part of the decision-making process.
5. Describe briefly what it takes to become a data scientist.
A lot of people think you need a deep math background, but really to get started all you need is a high school math education. What it really takes are analytical curiosity and not being afraid to get your hands dirty with truly understanding the data you’re working with. It also helps to have some SQL or database programming experience, even though the languages you’ll use most as a data scientist will be slightly different. But, the heart of Data Science is about uncovering things, so if you consider yourself an ‘explorer’ and have a healthy skepticism about things and ask a lot of questions, data science might be right for you. In my experience, I’ve found that asking the right questions is the key to uncovering really meaningful insight.
6. Do you think one day robots will be smart enough to take over the world?!
No, I don’t, but I’m hoping the robot I’m building at home will be smart enough to drive itself. It’s kind of a pet project I’m working on with my daughter, but I’m hoping that through deep learning it will eventually be able to drive me to work- kinda like a home grown self driving car!
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