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Mid LevelFull-timePythonMachine LearningData ScienceTensorFlowPyTorchAIMLNLPData
Salary Range
$80,750 - $109,250 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Data Scientist to join our Customer Support team at Airbnb. This role focuses on building scalable and robust systems to match our services to specific customer needs, creating meaningful impact through deep scientific understanding and designing interventions for Airbnb CS’s most critical challenges.
Key Responsibilities
- →Build ML/LLM models to understand customer issues and identify the most important areas to prioritize for resolutions.
- →Leverage generative AI methods to understand customer service experiences based on diverse datasets, and identify failure modes and opportunities for improvement.
- →Implement advanced techniques to automate the evaluation of LLM, ensuring high efficiency and quality.
- →Identify high-impact business opportunities through data exploration and prototyping, translating business problems into scientific formulations.
- →Collaborate closely with cross-functional partners—including software engineers, product managers, operations, and analytics—to refine ML/LLM requirements, drive scientific decisions, and quantify business impact.
- →Develop, productionize, and operate models and pipelines at scale for both batch and real-time use cases, structured and unstructured data.
- →Build scalable performance measurement solutions for LLM evaluation using internal tooling, integrating industry best practices and state-of-the-art innovations.
- →Use AI to automate repetitive data science workflows and enhance efficiency.
Requirements
- ✓2+ 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 (e.g. training/serving, feature engineering, feature/model selection, labeling, A/B test), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, personalization and recommendation).
- ✓Proficiency with LLMs and/or related AI, NLP. For example, BERT, GPT-2/3/4, LLaMA, Mistral.
- ✓Proven ability to communicate clearly and effectively to audiences of varying technical levels, observation causal inference skill is a plus.
- ✓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.
- ✓Ability to take a product-oriented mindset in using conceptual and innovative thinking to develop and apply solutions taking into consideration the user experience.
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