About the position:

Trust is at the foundation of every Airbnb experience and as such we aim to make it the most trusted platform in the world. As such, experimentation is core to our growing business. We want to take a scientific approach to decision-making through careful hypothesis generation and testing and drive actions/refine strategies through insights from experimental analysis.

Our inference data scientists understand the complications of running experiments in a two-sided marketplace, power analysis and stopping criteria, and statistical models to improve power/significance. Another interesting problem space is understanding what to do when we are unable to conduct experiments. How do we understand the impact of something new? You will be deeply involved in the technical details of building highly available and real-time risk detection services to understand ever evolving attack vectors and to keep Airbnb a safe and trusted community.

Responsibilities:

• Design experiments to understand the impact of user profile changes in complex and interlocking parts of the Airbnb action flows
• Maintain the right balance between speed to market and scientific rigor when designing solutions
• Define and evaluate key metrics and understand what moves them and why
• Investigate challenging questions around user experience to understand the voice of our users at scale
• Identify critical business problems and create analytical and modeling solutions to inform business decisions with compelling data stories
• Own conceptualizing, developing, and maintaining dashboards and visualizations
• Partner with Engineering to improve data source quality
• Empower the team to answer data questions quickly and easily by building high-quality ground truth data sets

Minimum Qualifications:

• 8+ years of relevant industry experience
• Expert in at least one programming language for data analysis (Python or R)
• Experience with experimentation and machine learning techniques
• Experience in schema design and high-dimensional data modeling
• Proven ability to succeed in both collaborative and independent work environments
• Passion for high data quality and scaling data science work

Preferred Qualifications:

• Strong skills in SQL and distributed system optimization (e.g. Hadoop, Hive, Spark, Presto)
• Experience with an ETL framework like Airflow
• Experience with causal inference and structural models
• Python skills preferred
• Experience with technical mentorship of other data scientists
• Experience with prototyping and writing production code

The starting base pay for this role is between $152,000 and $203,500. The actual base pay is dependent upon many factors, such as: education, experience, and skills. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits