Karolis Urbonas

Karolis Urbonas is currently leading a research science and analytics team in Amazon Alexa. He's a data science enthusiast obsessed with machine learning, analytics, neural networks, data cleaning, feature engineering, and every engineering puzzle he can get his hands on.

How to Lie with Data

By Karolis Urbonas, Amazon on April 20, 2017 in Confirmation Bias, Data Visualization, Mistakes, Overfitting
We expect data scientists to be objective, but intentionally or not, they can produce results that mislead. We examine three common types of “lies” that Data Scientists should be aware of.
Top mistakes data scientists make when dealing with business people

By Karolis Urbonas, Amazon on April 13, 2017 in Business, Data Scientist, Mistakes, Skills
There are no cover articles praising the fails of the many data scientists that don’t live up to the hype. Here we examine 3 typical mistakes and how to avoid them.
How to stay out of analytic rabbit holes: avoiding investigation loops and their traps

By Karolis Urbonas, Amazon on April 6, 2017 in Data Science, Methodology, Skills
Data scientists tend to think that their main job is to answer complex questions and gain in-depth insights, bu in reality it is all about solving problems – and the only way to solve a problem is to act on it.
What makes a great data scientist?

By Karolis Urbonas, Amazon on March 30, 2017 in Data Science Skills, Data Scientist, Skills
Here are 3 key traits that differentiate between a data scientist and a great data scientist, starting with – great data scientist is obsessed with solving problems, not new tools.
How to think like a data scientist to become one

By Karolis Urbonas, Amazon on March 23, 2017 in Amazon, Data Science Skills, Data Scientist, SQL, Statistics
The author went from securities analyst to Head of Data Science at Amazon. He describes what he learned in his journey and gives 4 useful rules based on his experience.

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