When is data science a house of cards?

As data scientists, when we reach an answer, we often communicate that answer and move on. But what happens when there are multiple data scientists with varying answers? The expense of replicating and testing the quality of work often leaves critical business challenges unstaffed. At Pinterest, we lowered the cost of replication to the point that could afford to run an experiment. So we did. We asked nine data scientists and machine learning engineers the same question, in the same setting, on the same day. We received nine different results. Reducing the costs of data science   In order to efficiently replicate results nine times, we used a new method of iterative supervised clustering. It’s phenomenally easy to grok and comes with a three step Python notebook with pre-loaded data.…


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