Senior Data Product Manager - AI/NLP Data Platforms

IV.AI; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

IV.AI in the United States seeks a Product Manager to own a core data product line—from data capture through client-facing insights—for blue-chip clients. You will read data, diagnose anomalies, and partner with engineering on schema, pipeline design, and validation.

You will drive growth, measure funnel, coverage, and data freshness, and translate capabilities into dashboards and specs for cross-functional teams. Proficiency with SQL, data contracts, and AI-enabled tooling is a plus.

Qualifications

• Bachelor's degree in a relevant field.
• 4–6+ years in a Product Manager role or hybrid technical/product role in a small team.
• Strong technical and data fluency; able to read SQL and discuss data pipelines and schemas with engineers.
• Experience owning a product end-to-end with measurable outcomes.
• Data-driven with metrics to drive prioritization (funnel, quality, usage).
• Excellent written communication; able to create specs and dashboards for technical and client audiences.
• Familiar with Linear and Notion and comfortable using AI tools in workflow.

Responsibilities

• Own roadmap from data acquisition to client-facing insights.
• Define schemas, contracts, and validation with engineering.
• Partner with cross-functional teams and align on data contracts.
• Write specs, define dashboards, and decide what ships.
• Use AI tools to improve the product workflow.

Skills

SQL literacy

Data fluency

Product ownership

Metrics-driven

Technical communication

AI tools usage

Education

Bachelor's degree

Tools

Linear

Notion

BigQuery

PostgreSQL

Claude

Job description

IV.AI in the United States seeks a Product Manager to own a core data product line—from data capture through client-facing insights—for blue-chip clients. You will read data, diagnose anomalies, and partner with engineering on schema, pipeline design, and validation.

You will drive growth, measure funnel, coverage, and data freshness, and translate capabilities into dashboards and specs for cross-functional teams. Proficiency with SQL, data contracts, and AI-enabled tooling is a plus.