Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. It takes a unified team committed to our core values to achieve this goal. Airbnb's various functions embody the company's innovative spirit and our fast-moving team is committed to leading as a 21st century company.
Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb.
As an ML Data Scientist in the Platform team you will work with a diverse collection of structured and unstructured data to design, build, and support machine learning models. You will collaborate with a strong team of engineers, product managers, designers and operation agents to incorporate these models into scalable and robust systems that enable exceptional product experiences.
The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of Machine Learning practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us.
Typical ML Challenges Include
- Operate on the cutting edge of modern ML and build novel high-ROI features such as embeddings that can be shared in use cases across the company
- Developing NLP models to add intelligence to Airbnb's interactions with guests and hosts in messaging, customer service and more.
- Building machine learning models to detect high risk activities like account takeovers, fake contents and fraudulent transactions, or high risk entities like fake accounts or stolen cards.
- Utilizing Deep Learning techniques for advanced feature engineering and model building; e.g. how to model for user behavior sequences.
- Working cross functionally with operations and product teams to define and collect labels for model training; leverage active learning and other human-in-the-loop techniques to improve ML efficiency.
- Developing machine learning models to interact with the right users using the right content at the right time through the right marketing channels to optimize Airbnb’s long term business impact, such as Guest Booking Propensity Model, Churn Prediction Model, Guest to Host Propensity Model.
Traits We Value For This Role Include
- Advanced degree in a quantitative field, e.g. Computer Science, Operations Research, Mathematics
- 2+ years industry experience developing machine learning models at scale
- Experience taking research prototypes to production.
- Proven ability to design analytical solutions to complex business problems and to partner cross-functional peers to tailor those solutions for the greatest possible impact.
- Deep understanding of ML domains (e.g. NLP, computer vision, recommendation, anomaly detection, graph learning), algorithms (eg. deep learning, gradient boosted trees, optimization), and best practices, (e.g. skew minimization, A/B testing, feature engineering, model selection)
- Strong programming (Python / Scala / Java / C++ or equivalent) and data engineering skills
- Utilize OSS ML technologies such as PyTorch, TensorFlow, Spark, Airflow
- Versatility to communicate clearly with both technical and non-technical audiences.
- Publications or presentations in recognized Machine Learning and Data Mining journals/conferences 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
The starting base pay for this role is between $152,000 and $203,500. The actual base pay is dependent upon many factors, such as: education, experience, and skills. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status