Staff Data Scientist

Summary

Join Airbnb's Marketing Technology team as a senior-level Data Scientist to build cutting-edge personalization and measurement capabilities. You will leverage AI, LLMs, and advanced segmentation algorithms to create innovative solutions for understanding user behavior and preferences. This role involves extracting signals from large datasets, translating insights into actionable strategies, designing and running experiments, and collaborating with engineers and stakeholders. You will also mentor junior team members and contribute to Airbnb's scientific community through publications. The position is US-remote eligible with a preference for West Coast hours. Compensation includes a competitive salary, bonus, equity, benefits, and Employee Travel Credits.

Requirements

• 9+ years of relevant industry experience (e.g. ML scientist, tech lead, junior faculty) and a Master’s degree or PhD in a quantitative field
• Working experience in marketing
• Deep understanding of personalization
• Ability to model the customer journey using mechanisms, such as Markov Models, that combine a knowledge of the customer’s current state along with future potential states
• Hands-on experience with Machine Learning best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization)
• Hands on experience with large language models, i.e. BERT, LaMDA, GPT-2/3/4, LLaMa
• Strong fluency in Python or R for hands-on IC work and advanced data analysis in SQL at scale
• 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, that demonstrates an eagerness to learn and share
• Knowledge of experimentation and statistical biases
• Familiarity with multi-sided marketplaces

Responsibilities

• Extract signals from large-scale structured, unstructured, and click-stream data to generate insights for improving the targeting and efficiency of Airbnb communications and actions
• Work with our business partners to translate insights into actions and build tests to demonstrate and measure the efficacy of those actions
• Demonstrate good judgment in selecting and evaluating methods and techniques for obtaining solutions
• Design, run, and diagnose experiments to validate hypotheses and performance of data prototypes
• Design systems to optimize marketing engagement with users
• Work closely with the ML Engineering team as a science partner to prototype machine learning use cases for use in the product, and work with stakeholders to iterate on requirements
• Build data products to understand users’ intentions and preferences at various stages of the user-product journey
• Research, present, and publish internally and externally, to engage and advance Airbnb’s standing in the scientific community
• Focus time – Build machine learning prototypes, develop data mastery to uncover learnings, and formulate structured frameworks to classify our users’ online product experience and interpret their behaviors
• Autonomy – Apply and investigate state-of-the-art innovations to uplevel Airbnb status-quo approaches to technical problems
• Influence – Clearly scope the technical solutions, milestones of long term innovative projects and align with stakeholders for adoption
• Communicate - Regularly present work internally in 1:1’s as well as  monthly meetings to technical, engineering and product stakeholders.  Inform our business partners and stake holders on our progress, generate excitement on roadmap and build collaborations
• Mentorship – Provide technical guidance to junior team members and be accountable for the project outcome
• Publish externally and engage with the scientific community to advance Airbnb’s standing

Benefits

• Bonus
• Equity
• Benefits
• Employee Travel Credits