Airbnb Staff Data Scientist Supply Growth 

United States 

291302682

The Difference You Will Make:

As a Staff Data Scientist, you will be hands-on and responsible for building the data products, inference frameworks, and intelligence to power and inform supply growth levers. You will work centrally, amongst other data scientists, while partnering cross functionally with design, product, and engineering to deliver initiatives such as:

• Performing analysis and developing models to inform how to bring high quality supply onto Airbnb, and how to best merchandise and showcase this supply to our guests.
• Creating measurement frameworks and/or designing experiments to access the tradeoffs and the incremental benefits of new growth levers.
• Building and operationalizing systems to identify suboptimal host products and formulating end to end solutions to improve them.
• Providing mentorship to other data scientists, exemplifying a high bar for technical excellence.

A Typical Day:

• Insights: Generate insights around our supply to discover ways to continually improve our marketplace
• Measurement: Apply causal inferences methods and/or design experiments to estimate the effect of Airbnb's growth levers
• Build: Develop inference frameworks, models, prototypes and data products to scale your ideas
• Communicate: Regularly present technical work to stakeholders to generate excitement and get buy-in on ideas

Your Expertise:

• 9+ years of relevant industry experience, ideally with a Master’s degree or PhD in a quantitative field
• Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
• Experience with inference and machine learning techniques
• Experience with the end-to-end lifecycle of building statistical and ML solutions from ideation phase, to prototyping, to testing / evaluation, to deployment in production
• Proven ability to succeed in collaborative environments with cross-functional stakeholders and also in independent work environments
• Proven ability to communicate clearly and effectively to audiences of varying technical levels