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Working with DataRobot software

Working with DataRobot software

Hello, I am a student of Data Science and this week I was offered my first job in the area. The job is in a consulting company to work with a partner that has bought the software DataRobot and they need a team to operate it. I never heard about this software before. Did some research and apparently this software do the job of a data scientist. So I am afraid that I will be a monkey pressing buttons and not really work applying my data science skills. What do you guys think? Am I wrong?

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I think it is healthy to think of DataRobot as an additional tool in the datascience toolbox which helps with convenience. While DataRobot has a lot of great features which are usually cumbersome to do manually, it does benefit to have datascience knowledge when using the software. Knowledge about how many CVs to do, how large a holdout is important, along with the general working of the different models and types of regularization is important. 

Another thing to note is the Python API which I am loving. Training a bunch of models on the cloud with different splits with only a few lines of code is massively more convenient than loading all the various packages and doing all the model setup manually. 

Interpretation of ROC/Lift curves, residuals and other metrics is also very important when scrutinizing the different models. 

All in all, my experience tells that you don't have to worry about not using your data science skills.

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I think it is healthy to think of DataRobot as an additional tool in the datascience toolbox which helps with convenience. While DataRobot has a lot of great features which are usually cumbersome to do manually, it does benefit to have datascience knowledge when using the software. Knowledge about how many CVs to do, how large a holdout is important, along with the general working of the different models and types of regularization is important. 

Another thing to note is the Python API which I am loving. Training a bunch of models on the cloud with different splits with only a few lines of code is massively more convenient than loading all the various packages and doing all the model setup manually. 

Interpretation of ROC/Lift curves, residuals and other metrics is also very important when scrutinizing the different models. 

All in all, my experience tells that you don't have to worry about not using your data science skills.