Airbnb Staff Data Scientist Algorithms AirCover 

United States 

420444769

The Difference You Will Make:

For this role, we’re seeking an AI expert to join the AirCover Data Science team, and have a direct opportunity to contribute, influence, and lead by designing scalable scientific solutions for problems like:

• Develop accurate, agile, and explainable fraud detection systems to guard platform quality and protect guests and hosts
• Detect intents across various entry points with large-scale unstructured data using NLP methods
• Collect evidence from images and receipts to gauge monetary value of the request leveraging computer vision
• Optimize presentation of AirCover products through designing thoughtful user segmentation and personalization
• Route high-complexity issues to agents with personalized strategy, incorporating user history and agent performance
• Summarize customer journey and conversations with foundational or fine tuned large language models (LLM) to assist operation agents

A Typical Day:

• Identify high impact business opportunities through data exploration and model prototype, translate business problem into scientific formulations
• Work collaboratively with cross functional partners including software engineers, product managers, operations and research, to refine requirements for machine learning models, drive scientific decisions, and quantify impact
• Hands-on develop, productionize, and operate machine learning models on paved path, including both batch and real-time use cases, structured and unstructured data
• Regularly present work internally at monthly meetings 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

Your Expertise:

• 9+ years of relevant industry experience (e.g. ML scientist, tech lead, junior faculty) and a Master’s degree or PhD in relevant fields
• Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse
• Deep understanding of Machine Learning lifecycle best practices (eg. training/serving, feature engineering, feature/model selection, labeling, A/B test), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection)
• Proficiency with LLMs and/or related AI, NLP, CV, UGC/content understanding topics including deep learning, information retrieval, or knowledge extraction. For example, BERT, GPT, LLaMA, Mistral
• Comfort to collaborate with software engineers to understand complex systems and abstracted logs, proven ability to communicate clearly and effectively to audiences of varying technical levels
• Proven mix of strong intellectual curiosity with high level of pragmatism and engagement with the technical community. Publications or presentations in recognized journals/conferences is a plus

Offices: United States