(Contract) Senior Data Scientist, Platform Inference - MarTech DS Measurement

About the Role

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.</span></p></div><p><strong>The Community You Will Join:</strong></p> <p>MarTech Data Science Measurement empowers Airbnb to optimize marketing ROI by generating data-driven recommendations. We lead the way in defining and advancing best practices for measuring and optimizing marketing impact. We collaborate with Marketing, Finance, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements. Our team’s tenets are:</p> <ul> <li>Actionable: Deliver insights that drive confident business decisions.</li> <li>Impactful: Prioritize projects based on their expected value to Airbnb.</li> <li>Balanced: Adapt methods to business questions and data realities, acknowledging limitations.</li> <li>Rigorous: Maintain methodological integrity and quantify the sensitivity of findings.</li> <li>Innovative: Invest in advancing measurement science and developing new methods.</li> <li>Influential: Share learnings across Airbnb and the broader data science community.</li> </ul> <p><strong>The Difference You Will Make:&nbsp;</strong></p> <p>We are seeking an experienced <strong>(Contract) Sr. Data Scientist </strong>for a <strong>24 month contract</strong> with deep expertise in marketing measurement, with a particular focus on Marketing Mix Modeling (MMM) and geo-based causal inference. The ideal candidate brings strong statistical intuition and hands-on modeling experience to quantify the incremental impact of Airbnb's marketing investments across channels and geographies.

Key Responsibilities

• 1

  Develop and deploy ML models solving real-world product and business problems.

• 2

  Conduct exploratory data analysis and feature engineering on large datasets.

• 3

  Evaluate models using rigorous metrics, iterate based on offline and online experiments.

• 4

  Collaborate with product and engineering teams to integrate ML into production.

• 5

  Publish and present research findings internally and externally.

• 6

  Monitor model performance and retrain as data distributions shift.

Requirements

• Bachelor's/Master's/PhD in Statistics, Math, CS, or related field.
• Strong Python and ML library proficiency (scikit-learn, TensorFlow, PyTorch).
• Experience with large-scale data processing (Spark, BigQuery).
• Solid understanding of statistical modelling and A/B experimentation.
• Excellent communication skills with both technical and non-technical audiences.

Skills Required

How The Selection Process Works

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