Being Data Scientist doesn't necessarily mean being a Computer Expert.

In the linked Podcast, we have an example of someone that is driven by passion and hardworking. I find that there are two big insights to receive from it.

First, Data Analytics is a very wide area of study. One can prefer Python against R or Tableau, or all the way around. What really matters is the overall Goal of applying our knowledge to find a meaningful value for our objetive. As a result, we can learnt different tools, there is no a singular, special or important one.

Second, it is very important that we value ourself and what is our life experience. There are learnings even in hard times. When we try to approach the role of Data Scientist, we must rethink on what was the thing that involved and caught us about Statistics or Maths or Logistics or DataBases, etc. It is crucial that we say it, because is what identify us as unique.

Enjoy the podcast ;-)

#machinelearning #datascientist #interview #path #datascience