New Data Product Manager

Data Source Ownership & Methodology Design:

• Own translation of raw alternative datasets into scalable, AI-ready data products.
• Design methodologies to combine, normalize, and interpret disparate datasets.
• Partner with Data Engineering to shape source data into clean, well-structured datasets.

AI Product Intelligence & Knowledge Systems:

• Define how the product should use datasets including valid query patterns and guardrails.
• Own metric definitions and data lineage to ensure accurate and explainable answers.
• Establish standards for reasoning across datasets to prevent over-interpretation.

Product Development & Customer Problem Solving:

• Translate customer questions into scalable methodologies and product capabilities.
• Expand the range of questions the product can answer via new forms of segmentation and cross-dataset insights.
• Partner with cross-functional teams to identify new data sources and increase commercial value.

Data Quality & Operational Excellence:

• Coordinate testing and validation of staged data changes before production.
• Own incident management for data quality issues and methodology changes.
• Build and maintain quality checks tailored to AI-powered customer experiences.