Data Quality Lead

- Oversee ingestion pipelines for key data sources including Sayari, S&P, and Altana. - Liaise with internal and external stakeholders to ensure procurement tracking and data quality. - Monitor and resolve backlog issues in data quality logs. - Lead assessment of data quality for all GSCIP data through exploratory data analysis. - Track and log existing data quality issues in coordination with GSCIP data scientists and license users. - Prioritize issues based on feedback and raise them with suppliers, suggesting solutions. - Write pipelines to ensure ingested data meets expected formats and contractual criteria. - Conduct exploratory data analysis and anomaly detection to uncover unknown issues. - Produce dashboards and reports on data features of interest for GSCIP data scientists and users. - Develop reproducible pipeline functions for data quality features. - Investigate the value of each data source for future procurement strategy. - Track strengths and weaknesses of each data supplier. - Scope new data sources to address existing gaps and lead annual evaluations of datasets. - Conduct IRAP assessments for new datasets. - Maintain comprehensive documentation including data dictionaries and usage guides. - Collaborate with engineers and data scientists to support building robust data pipelines. - Explore new data sources related to risk and company intelligence. - Formalize ownership for unowned or informally managed datasets. - Design and deliver learning modules to enhance GSCIP data literacy.