Communication in Data Science (5 Tips)

Subscribe to RichardOnData here:    / @richardondata  

In this video, I discuss communication in data science (with a focus on communicating to clients and stakeholders, not necessarily with your team). This is not always discussed as often as statistics, machine learning, etc., but it's an equally important piece of the puzzle.

Five tips I have for current or aspiring data scientists are:

1) Move from thinking about "technical needs" to "business needs"
2) State your key assumptions
3) Empathize and build relationships with your stakeholders
4) Use (simple) visualizations
5) Tell engaging stories

More about communication and UX at:
Medium:   / a-data-scientists-guide-to-communicating-r...  
MartinSights: https://www.martinsights.com/?p=1256
Inside Big Data: https://insidebigdata.com/2018/03/28/...
Adobe: https://theblog.adobe.com/putting-per...

Books I recommend:
"The Visual Display of Quantitative Information" - Edward Tufte (https://amzn.to/3kVrR2o)
"Show Me the Numbers" - Stephen Few (https://amzn.to/3n2qTTU)