Two Phyla of Data Scientist

Data Science is a big umbrella that covers a range of specialities. However, I’ve noticed a high-level split between practioners which is based on their approach to data itself.

The first is driven by curiosity. They approach the dataset as an archeologist might a dig or a detective a murder scene. The exploratory tools of visualisation help them see patterns and number crunching lets them amplify detail. They wade in to the source and become experts in their data set, using tools to leverage their insight. They are ever-skeptical and pick at quirks. They build up a trusted toolkit to open up the data. What insights they unearth, they want to polish up and share, either with the business or the customer.

The second is driven by beauty. They take the raw material of a data set and aim to fit it to a model which is elegant and powerful. By careful tuning of parameters and ad hoc algorithmic cleaning they are able to filter out anomalies in the data and feed it into their algorithmic machinery. They strive for general solutions which transcend the arbitrariness of any particular data set. In this, they are forever exploring more powerful and ingenious algorithms and models.

Are you one of these, a hybrid or a different creature altogether?