This is where youI’ve spent 10+ years as a data scientist applying experimentation and causal inference to real product, growth, marketing, and platform decisions at companies including Atlassian, Pinterest, Google, eBay, and American Express.

I’ve designed and analyzed A/B tests, built experimentation best practices, developed proxy metrics for long-term outcomes, and used causal frameworks to answer questions when randomized experiments were unavailable or incomplete.

What I bring to this workshop is a practitioner’s perspective: causal inference is not just academic theory, it is a decision-making toolkit for messy real-world environments where stakeholders need credible answers.

My goal is to make causal inference practical, intuitive, and directly useful for business problems, interviews

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