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A couple of months ago I read about the Infinite Game, a book that changed my life by introducing me to the mindset adopted by those who win. Success isn't a destination, but an endless journey of improving yourself. In the spirit of continuous improvement I've created this resource, a continuously updated page on the various skills I learn and the resources I use to become a better analytics practitioner.
At their core, someone who works in data science is someone who regularly uses data to help derive and present insights to their stakeholders. In their book Build a Career in Data Science, Emily Robinson and Jaqueline Nolis split the career of Data Science into three main roles:
Data Analysts: Takes data from a raw source and brings it to a business users. Typical skills include:
Decision Scientists: Takes a large set of data and tries to help a business make a decision such as factory locations, traffic in stores or future revenue. Typical skills include:
Machine Learning Engineers: Take a dataset and make it continuously provide value to the business like the people working on Netflix's recommendation algorithms. Typical skills include:
Build a Career in Data Science
Basic Structure Machine Learning/Deep Learning