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How Do You Know if You're Cut Out To be a data scientist?

Predictive Analytics, data scientist, analytics, data science, machine learning | [fa icon="comment"] 0 Comments

Just think, 50 years ago, the personal computer had only just been invented. Unless you were NASA or the US military, then you probably didn’t have one.




Now fast forward to today. Almost everyone has one, or three. If you include the computer in your car, the smart devices at home, any wearables, then you’re creating a lot of data, all the time. So what does this all mean for you?




If HBR is anything to go by, then data science is the sexiest job of the 21st century. So I interviewed one of our top data scientists David Duan at Mindfull to get an inside view of what it takes to be a data scientist, and while you need to know a lot about machine learning, artificial intelligence, data mining, OLAP etc (see here for a scarily long list of terms), the key skills to be a data scientist are much more simple.


In third place: You must be close friends with numbers - You see, numbers are sexy. They tell you something. They hold meaning. They don’t lie (for the most part). Mathematics and statistics, even physics will be your friend. You will need to learn how to use software that deals with predictive modelling and technologies like Hadoop, Cassandra, and Cloud solutions - all of which deal with numbers. So to start off, make sure you have an interest in numbers.


In second place: Be obsessed with the meaning behind the number. Numbers tell a story, they can show you what a customer is doing, where, when, how, even why they are doing it. From here you can use mathematics to build a model, and test your hypothesis. “I find this process really fascinating and really exciting - especially when you find something new and nobody else realises.” - David Duan




In first place, is the skill that sets us apart from other animals: The ability to communicate complex concepts well. See, to be a great data scientist, you don’t just get given the right data, direction on what to do with it, and most likely, you won’t get listened to automatically. You need to be a strong communicator to get rights to particular data in the first place. You need authorisation to access the data, because a lot of information is confidential. Then you then need to convey what you find back to your team in a simple way, while understanding that not everyone is as good at numbers as you are.

Perhaps your organisation has data you are collecting, but are unsure of how to use it. Mindfull has a team of data scientists who can help, speak to us today.



Topics: Predictive Analytics, data scientist, analytics, data science, machine learning

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