We are currently seeking Data Science leaders for each of the teams listed below, relevant domain experience is a plus:
Search team: The backbone of Airbnb’s business is its search algorithm - a sophisticated model that aims to match guests and hosts for a given trip or experience. It is a problem that combines online and offline worlds in a way that few other businesses have exposure to, which presents unique challenges in personalization, analysis and measurement.
Risk team: Airbnb has unique risk opportunities combining online and offline. It must be vigilant of the typical online marketplace security risks while also facilitating trusted experiences happening offline in over 34,000 cities. A few examples of this team’s work include identifying: payment fraud, phishing attacks, user account takeovers, fraudulent listings, and fraudulent reviews. Most important, however, is reducing risk to people or property before an incident occurs. This team is part of trust team whose goal is to keep Airbnb a safe and trusted community.
Payments team: Airbnb has become a global platform connecting people to unique travel experiences, at any price point, in more than 34,000 cities and 190 countries. The data scientists in this space work on growing Airbnb profitably by addressing questions like which payment methods to adopt for stimulating growth, build machine learning models to optimize transaction routing to processors and find anomalies in transactions, build recommendation engine to suggest appropriate methods and models and advise business development team on payments partnerships.
Foundation team: This team is responsible for scaling data science and machine learning. You will work in partnership with the engineering team to build shared machine learning infrastructure, implement cutting edge statistical models into data science tools more broadly, and work with cross functional executives to design strategy to empower the data science team and the company at large.
Some examples of traits we value:
5+ years of industry experience, 2+ years hands-on management experience
PhD, Masters or equivalent work experience in a quantitative field preferred
Passion for scaling data work and improving the efficiency of teams
Strong understanding of statistics and machine learning
Keen eye for detail and thoughtful investigation of data before relying upon it
Intuition for data science best practices, stemming from proven experience
Steadfast focus on creating impactful change
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