Tom Merritt asks the five questions every data scientist should be able to answer.
Data scientists are increasingly important to organizations as decisions become more data driven. You need to be able to tell the real and talented data scientists from a charlatan who talks the talk. Here are five questions every data scientist should be able to answer.
- What is data science, and how does it differ from data analysis? It's one thing to say you can look at data and tell what it means. It's another thing to be able to show replicable results and develop new methods for discovering things.
- What can't data science do? A real data scientist will easily be able to describe the limits of data science today and what progress is being made.
- How do we balance privacy with collection? This should be top of mind for all data scientists, if for no other reason than dealing with GDPR. On the flip side, any data scientist who claims to have perfectly solved this balance should be viewed with extreme skepticism.
- What data is most useful for my business? Collecting data can be the easy part even today. Deciding what data to collect because it's valuable is where the science comes in. It's tempting to just collect it all and worry about it later, but that's not only increasingly more unpopular, it slows things down as well.
- What production-level machine learning techniques do you work with? Unless you're specifically hiring a research data scientist, you need to know that the person can carry out concrete applications.
SEE: How to build a successful data scientist career (free PDF) (TechRepublic)
Data science is extremely valuable and yes, "what's your favorite algorithm?" is a decent question to ask them too, but hopefully these five questions will help you find a top-notch data scientist.
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