Airbnb Staff Data Scientist – Algorithms Trust 

United States 

264607501

A Typical Day:

• Build machine learning models to detect high risk activities, develop data mastery to uncover learnings, and formulate structured frameworks to classify and interpret our users’ behavior
• Work cross functionally with operations and product teams to define and collect labels for model training, optimize effectiveness of manual review, and build self-satisfiable verifications that scale.
• Develop measurement strategies to test new product features that deter and mitigate risk, while adhering to ethical guidelines
• Apply and experiment with state-of-the-art innovations to uplevel Airbnb status-quo approaches to technical problems
• Regularly present work internally to technical, engineering and product stakeholders to iterate and generate excitement on roadmap progress
• Publish externally and engage with the scientific community to advance Airbnb’s standing
• Devise optimization models to make optimal business decisions while minimizing risk
• Utilize Deep Learning techniques for advanced feature engineering and model building, e.g., how to model for user behaviors sequences, or how can we detect anomalies effectively

Your Expertise:

• Advanced degree in a quantitative field. PhD is a plus.
• 9+ years of relevant industry and/or academic experience developing scientific frameworks, building machine learning models, and implementing advanced experimentation techniques (e.g. ML scientist, tech lead, junior faculty)
• Strong fluency in Python or R for hands-on IC work and advanced data analysis in SQL at scale
• Deep understanding of modern machine learning techniques and their mathematical underpinning, such as classification, clustering, optimization, deep neural network and natural language processing
• Comfortable collaborating with software engineers to understand complex systems and abstracted logs
• Proven ability to create and drive technical and impactful roadmaps for the business, and lead seamless execution of it.
• Proven ability to communicate clearly and effectively to cross functional partners of varying technical levels.
• Prior experience working in Fraud, Trust & Safety or a related area is a plus.
• Experience with advanced experimentation techniques is a plus.
• Experience productionizing real-time machine learning models is a plus.