Principal Data Scientist

Responsibilities

• Design, build, and own tools that are leveraged across the team, such as models for forecasting change, optimizing spend allocation, marketing incrementality, and attribution.
• Design and execute experiments, from classic A/B tests to complex causal inference analyses, with full ownership of hypothesis development, experiment design, and results interpretation.
• Build metrics frameworks and measurement strategies, helping stakeholders understand what to optimize for and why.
• Collaborate with our ML organization on high-complexity technical challenges, bringing statistical rigor and causal reasoning to our work.
• Translate ambiguous, multifaceted business problems into clear frameworks that guide decision-making.

Languages