Data Scientist, New Grad 2018 - Algorithms
Airbnb’s mission is to connect people to unique travel experiences, in more than 34,000 cities and 190 Countries. We are making it possible for hosts to supplement their income while helping visitors from around the world experience neighborhoods and communities outside traditional tourist zones.
Here at Airbnb, we’re big fans of travel. We love thinking about the diversity of experiences our host community offers, and we spend a fair amount of time trying to make sense of the tens of thousands of cities where people are booking trips every night. The tricky thing is, most of us haven’t been to Cuba, so we try to come up with creative ways to help people find the experience they’re looking for in places they may have never been. The data science team works in tandem with product management, engineering, and design teams to solve these types of technical challenges.
We are looking for an outstanding data scientist with strong machine learning background to join our team.
Skills and Qualifications:
- Pursuing an advanced degree in CS, Math, Statistics, Physics, Economics or other quantitative field with an expected graduation date of Summer 2018.
- Strong skills in statistics, probability, and machine learning.
- Great communication skills, and experience telling stories with data.
- 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).
- Experience productionizing machine learning model is a plus.
- $2,000 yearly employee travel coupon
- Competitive salary
- Paid time off
- Medical, dental, & vision insurance
- Life & disability coverage
- Flexible Spending Accounts
- Apple equipment
- Daily breakfast, lunch, and dinner
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