Data Scientist shaping performance measurement and optimization for Universal Ads. Collaborating with Product, Engineering, and Data teams, focusing on large datasets and experimental analysis.
Responsibilities
Experience navigating and working with large data sets, and designing and analyzing experiments
Develop experimentation and causal inference frameworks to quantify the impact of new product s and advertiser-level performance ramps, including methods to address skewness and low-signal environments
Analyze large-scale identity, auction, and conversion datasets to uncover performance drivers, optimize advertiser ROI, and inform measurement and optimization roadmap
Support the development of advanced measurement methodologies ( e.g. Halo), collaborating closely with Product and Engineering to test, validate, and scale solutions
Translate analytical insights into production-ready features and system improvements
Stay current with advancements in data science, machine learning, and advertising technology, incorporating new methodologies and tools into the team’s workflow
Conduct rigorous analyses and communicate findings clearly to technical stakeholders, driving data-informed decisions across teams
Interacts and leads meetings with product and service teams to identify questions and issues for data analysis and experiments.
Requirements
Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field
10+ years of experience in data science, analytics, or applied statistics (or 5+ years with Ph.D.)
Proven ability to work with large, complex datasets
Proficiency in Python, SQL or R and statistical/machine learning libraries
Strong understanding of experiment design, causal inference, and modeling techniques (e.g., regression, uplift modeling, Bayesian methods)
Experience with data visualization tools (e.g., Tableau, Looker, Plotly) and storytelling for non-technical audiences.
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