Responsibilities

• Evaluate and improve our marketing measurement leveraging techniques such as MMM(Marketing Mix Modeling), MTA(Multi touch attribution) and incrementality testing
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends.
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python

Preferred

• Experience in using open source packages for incrementality tests(e.g. Meta’s Geolift, Google’s Causal Impact) and MMM (Google’s Meridian, Lightweight MMM or Meta’s Robyn)
• Master's or Ph.D. Degree in a quantitative field
• Experience with predictive modeling, machine learning, and experimentation/causal inference methods.