Data Scientist - Algorithms, Risk (China)
Trust is at the foundation of every Airbnb experience and as such we aim to make it the most trusted platform in the world. To achieve such goal, the Data Science team relies on a diverse collection of structured and unstructured data to design, build, and support machine learning models to detect and prevent potential negative experiences and fraud attempts.
As a Data Scientist working on Algorithms, Risk (China), you will have the opportunity to collaborate with a strong team of engineers to build scalable and robust systems to detect and mitigate fraud in China. You will be deeply involved in the technical details of building highly available and real-time risk detection services to understand ever evolving attack vectors and to keep Airbnb a safe and trusted community.
Some of the challenges you will face include:
- Building machine learning models to detect high risk transactions or users
- Formulate machine learning approaches while paying attention to business metrics (i.e. how we make the model product-ready and at same time quantify the business impact)
- Experimentation of product features to deter and mitigate risk
- Devise optimization models to make optimal business decisions while minimizing risk
- Innovate and make advances on adversarial modeling
Here are example traits we value:
- 4+ years industry experience developing machine learning models at scale from inception to business impact.
- 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).
- Experience productionizing machine learning model is a plus.
- Speaks fluent Chinese and proficient English.
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