Partner with internal teams in advanced analytics work including experimentation, measurement and modeling.
Identify key drivers and correlations to meta-build analysis models that can explain and predict marketing effectiveness.
Develop AI capabilities to identify and classify creative features for responsive ads, ensuring they are effective for diverse languages.
Build data and extraction pipelines to collect and evaluate structured and unstructured data.
Develop evaluation frameworks for large-scale models, new metrics, and investigate anomalies. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods.
Minimum qualifications:
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 qualifications:
Experience delivering meta-analysis, fully automated analytics pipelines or audience segmentation and propensity modeling.
Understanding of Bayesian approaches and modeling frameworks.
Ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross-functional stakeholders.
