A Quote by Scott Nicholson

Engineering, I think you can pick up. [A data scientist's] curiosity is built-in — © Scott Nicholson
Engineering, I think you can pick up. [A data scientist's] curiosity is built-in
Companies are getting bitten by hiring a data scientist who isn't really a data scientist.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
If you're a scientist, and you have to have an answer, even in the absence of data, you're not going to be a good scientist.
To make yourself a good scientist I would say first, you have to have curiosity. If you don't have any curiosity you better choose something else.
Data scientist is just a sexed up word for statistician.
As an undergrad, I studied engineering physics at the University of Oklahoma, and all my degrees are from engineering departments. My father wanted me to join him in the oil-field business in Oklahoma, but I wanted to be a scientist.
There is a rampant tendency in any industry where someone is trying to sell something with a bunch of data, where they cherry pick a little bit... bias a little bit. This becomes quite easy when there is an enormous amount of data to cherry pick from.
Well, I mean, I'm still a scientist, you know. I think once a scientist, always a scientist.
A scientist naturally and inevitably ... mulls over the data and guesses at a solution. He proceeds to testing of the guess by new data-predicting the consequences of the guess and then dispassionately inquiring whether or not the predictions are verified.
I personally think there's going to be a greater demand in 10 years for liberal arts majors than there were for programming majors and maybe even engineering, because when the data is all being spit out for you, options are being spit out for you, you need a different perspective in order to have a different view of the data.
Scientists have one thing in common with children: curiosity. To be a good scientist you must have kept this trait of childhood, and perhaps it is not easy to retain just one trait. A scientist has to be curious like a child; perhaps one can understand that there are other childish features he hasn't grown out of.
We should always be suspicious when machine-learning systems are described as free from bias if it's been trained on human-generated data. Our biases are built into that training data.
As a scientist, I want to go to Mars and back to asteroids and the Moon because I'm a scientist. But I can tell you, I'm not so naive a scientist to think that the nation might not have geopolitical reasons for going into space.
MapReduce has become the assembly language for big data processing, and SnapReduce employs sophisticated techniques to compile SnapLogic data integration pipelines into this new big data target language. Applying everything we know about the two worlds of integration and Hadoop, we built our technology to directly fit MapReduce, making the process of connectivity and large scale data integration seamless and simple.
Shiv Nadar University has five schools with 16 departments offering 14 undergraduate, 10 master's and 13 doctoral programmes. The demand for engineering courses - computer science, engineering, electronics, communication engineering, mechanical engineering - is slightly on the higher side compared to other engineering courses.
One scientist will interpret data one way, another in another way. One scientist may feel that an experiment is valid, another feels it's invalid. That's why scientists have discussions and put forward their opinions in conferences and papers.
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