How to Build a Data Science Team: Get a Data Dog
As you build a data science team, start with a data dog: someone who will hunt, dig up, and fetch missing data.
As you form a data science team, get a data dog. A data dog is a data entrepreneur—they dig up, sniff out, and fetch data. Along with decision-makers, a data dog is one of the first two people you should hire, way ahead of data scientists. In her essay, Cassie Kozyrkov, Chief Decision Officer for Google, suggests this. “Data engineer” and “decision-maker” are the first two of eleven roles to hire; data scientists are SEVENTH on her list.
In the digital economy, entire companies are “data dogs.” For example, Missing Maps is an open, collaborative project that fills in the missing pieces of the maps of the world. Doctors Without Borders, the American Red Cross, and the British Red Cross founded Missing Maps, which has added over 1 million kilometers of roads and almost 44 million buildings to publicly accessible maps.
If you live in a developed country, it might seem odd that there are missing areas on the map, but many of the most vulnerable parts of the world are unmapped. More complete maps help humanitarian organizations reach those in need. Missing Maps is just one of the thousands of initiatives built on data.
Data dogs are relentless. Last year, Missing Maps filled 5,930 gaps in Indonesia, a country plagued by poverty and battered by natural disasters, in a joint project with my company and Microsoft.
Picasso said, “the problem with computers is all they can do is provide answers.” Data science isn’t only about finding answers. It’s about uncovering new data, missing data, and asking questions. Data dogs who fetch and find them are the key to success with AI.
