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- Developed the first prototype model for targeting omni-shoppers, delivering strong offline results that justified advancing the model to online experimentation.
- Played a key role in launching a new model to 11 alpha advertisers by ensuring campaign QA, historical data availability, system enablement, and measurement frameworks were in place. It was later rolled out to a $300M+ product.
Developed an incrementality estimation and bidding approach using experimental lift data and an ensemble of conversion models, iteratively validating and tuning via backend tests to achieve a 10X lift in estimated incremental conversions.
2022-2025- Built a custom analysis workflow for omni-shopping backend experiments, enabling statistically rigorous evaluation of offline conversion lift at scale, supporting 4-8 experiments per month, and saving significant analysis time while accelerating model improvements.
- Unblocked statistically significant experimentation for an offline model by correcting measurement issues, expanding eligible traffic (~2.5X), and designing a fallback holdout approach, ultimately enabling the first valid results and supporting general rollout.