What You'll Be Doing

Drive strategy and insights through designing and leading experiments and translating findings into strategic direction
Master causal inference by applying advanced techniques to estimate long-term and heterogeneous treatment effects
Draw reliable conclusions in settings with selection bias or imperfect randomisation
Drive deep product insights by uncovering fundamental drivers of experiment performance and understanding feature success across users, markets, and timeframes
Use insights from past experiments to improve future decision-making

Requirements

Strong experience designing, running, and interpreting A/B experiments in production environments
Solid understanding of causal inference concepts
Ability to apply statistical thinking to messy, real-world product problems beyond ideal experimental setups
Great communication skills in person, writing, and code, with both technical and non-technical audiences
Problem solver with a deep analytical mindset
Creative and insightful thinking about business problems
Familiarity with SQL
Excellent people skills for collaborating with stakeholders to translate business needs into data science problems

Solve meaningful problems at real scale within a complex, always-on marketplace impacting millions daily
See your impact quickly by shipping, testing, and improving ideas in a low-hierarchy, high-ownership environment
Grow through challenges and ownership with strong career support
Work in a culture built for builders featuring high standards, collaboration, flexible working, and continuous learning
Competitive salary and equity options to share in the success you help create