Airbnb Data Scientist Martech Inference 

United States 

3468685

The difference you will make:

We are seeking an experienced Data Scientist with deep expertise in causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts.

• Actionable: Deliver insights that drive confident business decisions.
• Impactful: Prioritize projects based on their expected value to Airbnb.
• Balanced: Adapt methods to business questions and data realities, acknowledging limitations.
• Rigorous: Maintain methodological integrity and quantify the sensitivity of findings.
• Innovative: Invest in advancing measurement science and developing new methods.
• Influential: Share learnings across Airbnb and the broader data science community.

A typical day:

• Causal Inference: Apply and develop causal inference methods to estimate the effectiveness of Airbnb’s marketing initiatives.
• Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts.
• Experimentation: Design and analyze experiments to evaluate the impact of marketing campaigns.
• Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies.
• Thought Leadership: Lead the creation of internal white papers and contribute to Airbnb tech blog posts.

Your expertise:

• PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience.
• Deep knowledge of causal inference methodologies and experimentation techniques.
• Proficiency in statistical programming (Python or R) and database usage (SQL).
• Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
• Proven track record of solving business problems through data science methods.

Preferred expertise:

• PhD in Economics, Statistics, Marketing, or a related field.
• Passion for marketing and consumer science, with a desire to stay informed about the latest academic research.
• Familiarity with Bayesian modeling and its applications in marketing.
• Experience with causal ML modeling.
• Experience in developing end-to-end models for data-driven decision-making.

Offices: United States