Leverage modern causal inference and marketing statistical methods to build intelligent, adaptive systems at scale
Collaborate closely with data analysts, account managers, product teams and engineering to understand business needs and iterate on solutions
Work with senior team members and product stakeholders to develop prototypes and take early-stage ideas through to production
Take ownership of core advertising measurement products to expand capabilities and improve performance
Explore data and systems, prototype ideas, run experiments to validate them and propose new products or advancements
Expand the causal inference and attribution-based measurement platform
Requirements
Bachelors in Statistics, Computer Science, Economics, Operations Research, or similar quantitative field (graduate degree preferred)
Solid understanding of modern data science, AI and machine learning
At least 3 years of experience with applying modern statistical marketing models, Bayesian statistics, and causal inference to solve complex, data-driven problems
Programming proficiency (preferably Python, its data science stack, and SQL) and desire to write production code
Excellent communication skills and the ability to present methodologies and findings to audiences with varying technical backgrounds
Experience working in modern cloud infrastructure environments like AWS and GCP is a big plus
Familiarity with the digital media / advertising industry is a big plus
Must be located in the United States (Remote - US Only)