Airbnb Staff Data Scientist Inference 

United States 

687237748

A Typical Day:

• Inference: Apply or develop causal inference methods, bayesian regression models to estimate the effect of Airbnb’s online and offline advertising
• Experimentation: Design and analyze experiments to measure the effectiveness of our digital marketing spend
• AI/ML: Use LLM to understand user travel scenarios and preferences and optimize marketing touch points .
• Insights: Generate insights about customer segments and the company's most valuable guests to improve ad effectiveness and optimize spend
• Communication: Work closely with a range of stakeholders to design and implement measurement of brand marketing campaigns
• Empowerment: Think strategically about opportunities to improve and scale our brand measurement and customer insights

Your Expertise:

• 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
• Strong fluency in Python or R for hands-on IC work and advanced data analysis in SQL at scale
• 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.
• Comfort to collaborate with product managers and software engineers to design and understand complex systems
• Knowledge with Bayesian Modeling, MMM and multi-sided markets.
• Strong knowledge of causal inference, statistics and experimentation
• Skilled in statistical programming (Python or R) and database usage (SQL)
• Ability to solve business problems using appropriate methods and models
• Ability to communicate clearly and effectively to cross functional partners of varying technical levels and drive impact
• Ability to translate complex findings and results into a compelling narrative. Proven ability to communicate clearly and effectively to audiences of varying technical levels.

Preferred qualifications

• PhD in Economics, Statistics, Marketing, or related field
• Passion for marketing and consumer science; a desire to keep up with and find opportunities to apply academic research