Principal Product Manager - Data

HG Insights is a leader in technology intelligence, providing data-driven insights that help businesses make strategic decisions about technology investments and market opportunities. The Principal Product Manager - Data will define and implement HG’s data roadmap, focusing on transforming raw data into predictive intelligence to drive customer outcomes.

Responsibilities:

• Define and implement the rolling 12 month data roadmap, central to HG’s product offerings, focused on an AI first strategy for data acquisition and data quality, evolving insights to meet customer needs, and improvements to customer delivery endpoints such as data feeds and API/MCP
• Be a champion of HG customers to ensure HG’s datasets and insights directly enable and drive ROI for B2B technology use cases such as account prioritization, pipeline acceleration, and territory optimization
• Work with the Office of the CTO on the implementation of vetted AI-driven product opportunities (e.g., automated tech-stack detection, buying-stage prediction, intent topic extraction)
• Work with the HG executive team on roadmap definition, progress updates, and alignment to the overall company strategy
• Collaborate with HG Marketing and Customer Success teams to articulate the value of data and AI-driven insights in sales-enablement contexts
• Stay ahead of emerging AI/ML trends and generative-AI techniques, assessing their commercial relevance for HG’s data offerings
• Represent HG externally as a thought leader in data intelligence and applied AI for B2B technology markets

Requirements:

• 10+ years of product-management experience in data, AI/ML, or analytics platforms
• Demonstrated success leading data-first product portfolios from vision through scaled delivery
• Experience collaborating with or within companies like ZoomInfo, 6sense, Demandbase, or similar RevTech leaders
• Strong technical fluency across data architecture, model lifecycle management, and cloud data platforms (AWS, GCP, Snowflake, Databricks)
• Understanding of machine-learning fundamentals (model evaluation, feature selection, supervised / unsupervised learning, LLM integration)
• Familiarity with GTM and revenue-intelligence ecosystems—how B2B data drives lead scoring, segmentation, and predictive sales motion
• Exceptional communication skills, capable of bridging executives, data scientists, and commercial teams
• Bachelor's degree in Computer Science, Engineering, or Data Science (advanced degree preferred)
• advanced degree preferred