The role involves working hands-on with large-scale consumer and behavioral datasets to support measurement products. The individual will evaluate existing data preparation and validation methodologies while identifying opportunities for improvement. Responsibilities include designing and prototyping new statistical approaches to address market challenges and developing performance indicators for product accuracy. The position requires investigating data issues, performing root-cause analysis, and recommending corrective actions. Additionally, the role entails partnering with cross-functional teams to support the production deployment of new solutions. Clear communication of findings to stakeholders and the maintenance of documentation regarding methodologies and best practices are essential components of the work.

The role requires three to six years of experience in a data science or statistical analytics position. Candidates must possess a strong foundation in statistics, mathematics, econometrics, or data science. Advanced proficiency in Python for data manipulation and validation is necessary, alongside a strong working knowledge of SQL for querying complex datasets. Furthermore, the position requires hands-on experience with data cleaning, validation, and quality control in cloud environments such as Azure and Databricks, as well as familiarity with version control using Git.