Software Engineer, Data (Machine Learning, Ranking, Analytics) airbnb
Why is data important at Airbnb?
Airbnb facilitates the travel experience from start to end (discovery, booking, during the stay, and collecting feedback). No other travel service participates so broadly in the travel experience. During all parts of the experience we are collecting data that we leverage to improve the effectiveness of our marketplace.
What are examples of work that data engineers have done at Airbnb?
We are using machine learning to score suspect reservations based on dozens of signals. Suspect reservations are then investigated by the Trust & Safety team.
We built a framework for A/B testing variations of our search ranking algorithms. At any given time we have several proposed changes being tested in production. The results of these experiments have improved our search conversion rate by 12% over three months.
We built a data warehouse using a star schema to track performance and corresponding meta data of our pay-per-click marketing campaigns. Star schema enables us to track performance at the most granular level while enabling us to pivot on any number of dimensions.
We built a predictive model to compute the relevance of geographic locations in Search by mining a year of our search log and reservation data: http://nerds.airbnb.com/location-relevance/
The following experience is relevant to us:
Strong CS fundamentals, including good working knowledge of classic algorithms and data structures
Past experience designing sophisticated search systems or working with big data
Quarterly employee travel coupon
Paid time off
Medical, dental, & vision insurance
Life insurance and disability benefits
Flexible Spending Accounts
Company sponsored tech talks and happy hours
Breakfast, lunch, and dinner
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