Airbnb has become a global platform that connects travelers and hosts from over 81,000 cities. The Lux Team is focused on offering transformative end-to-end trips through elevated homes, personalization & world class service. We're re-imagining the luxury space, and deciding how Luxury Retreats and Airbnb can join forces to create the best luxury travel experience possible.
As a data scientist in algorithms, you will have the opportunity to leverage Airbnb's rich data and state-of-art machine learning infrastructure to develop data products that are used by millions of users and propel the growth of our business. You will collaborate with a strong team of engineers, product managers and fellow data scientists in defining the frontier of data products in matching marketplaces. Data scientists will work on how to evaluate potential approaches, build features, algorithms, and determine metrics which are critical for machine learning models.
We have multiple openings available. Sample projects include:
* Improve search ranking features * Determine novel metrics to evaluate pricing models. * Build new model to predict the quality if the guest experience * Extract/summarize interested information from unstructured dataset
Here are some qualifications we look for:
* 4+ years experience developing machine learning models at scale from inception to business impact. Leadership opportunities also available. * Advanced degree in quantitative field. * Deep understanding of modern machine learning techniques and their mathematical underpinning, such as classification, recommendation systems and natural language processing. * Proven ability to tailor machine learning solutions to business problems in a cross functional team. * Experience with distributed machine learning and computing framework (Spark, Mahout or equivalent). Applied experience preferred. * Strong programming skill (Python, R, or Scala preferred). * Industry experience in developing deep learning model is a plus
Airbnb is a company that provides an online marketplace and hospitality services.