Kaggle recently pointed me at an interesting article on how Airbnb built their data science team, “Building a Team from the Inside Out: Alok Gupta on the Evolution of Data Science at Airbnb”.
There are a few interesting take aways from the article worth noting:
centralized team of data scientists to smaller embedded teams which sit within product area
Data Scientist is broken down into 4 specialized roles:
- Data engineers – They take messy data and transform it for analysis.
- Product builders – People who build data products that are user-facing. For example, they may build a recommender engine.
- Data analysts – They provide chief analyses outlining where opportunities lie for the business.
- Data experimenters – Scientists who know how to design and perform an experiment.
A number of tools are referenced in the article:
Key however, seems to be Airbnb’s “knowledge sharing tool” that allows data scientists to “write up analyses from start to finish” – effectively a blog of research. I would assume this comes with a fully repeatable way of anyone in Airbnb taking the research and branching down other roads, offering easy Return on Investment (ROI). In many ways similar to Kaggle Kernels and Datasets. Some details of the Airbnb sharing knowledge pipeline are discussed here.
Posted in Data
Tags: BigData, MachineLearning
