Responsibilities

• Partner with Growth Marketing and Product teams to analyze and optimize the end-to-end shopper journey, from acquiring new shoppers to driving repeat purchases.
• Develop user segmentation and propensity models to power personalized marketing campaigns, targeting shoppers with the right product at the right time.
• Collaborate with engineering and marketing to determine the signals we need to ensure we are connecting creators and viewers with the right offers at the right time.
• Develop and own the LTV models for YouTube shoppers, providing a critical input for long-term planning and investment.
• Design incentive programs experiments and optimize life-cycle communications with incentives.

Requirements

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

Preferred

• 5 years of experience in the consumer tech, media, or entertainment industry.
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience in causal inference techniques with a proven track record of applying them to solve business problems.
• Experience with advanced modeling techniques, including Marketing Mix Modeling (MMM), user LTV forecasting, and churn prediction and in e-commerce, retail analytics or two-sided marketplaces.
• Excellent communication and presentation skills, with a knack for distilling topics into simple, powerful messages.