Senior Product Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the Person Data strategy, including the roadmap, monthly priorities, outcomes, and metrics for accuracy, coverage, freshness, and compliance.

• Collaborate with Person Data product management, Privacy, Trust, Identity engineering, and cross-functional teams to execute the roadmap.

• Create and manage the AI evaluation engine, defining correctness, curating golden sets and trap records, setting up LLM-as-judge gates and confidence thresholds, and monitoring precision, recall, and production drift.

• Lead the shift from deterministic selection rules to agent-based inference using comprehensive evidence.

• Draft agent policy clauses, research grading guidelines, and pipeline acceptance rules; validate changes in shadow mode and phase out legacy logic when appropriate.

• Integrate AI and traditional tools thoughtfully, taking into account cost per row, latency, determinism, and auditability.

• Address entity-resolution challenges such as person-to-company matching, incorrect company links, duplicate individuals, and cross-source identity issues.

• Manage the privacy roadmap for person data, which includes suppression, opt-out, and notification processes, in collaboration with Legal and Privacy teams.

• Develop prototypes of adjudication agents, evaluations, and analyses in code utilizing AI engineering and data science; engage with Claude and agentic tools on a daily basis.

• Facilitate cross-functional execution across engineering, Match, Research, Data Science, Web Data acquisition, Privacy, and application teams.

• Articulate the rationale behind the roadmap to product and data leadership, and prepare release notes and customer-facing narratives in conjunction with Product Marketing.

• Report to the Senior Manager of Product for Core Data within the Core and Global Data organization under the Chief Data Officer.

⛳️ Requirements

• At least 8 years of product management experience, with significant time spent managing data products or data platforms at scale.

• Practical experience with data pipelines, preferably incremental or streaming rather than batch rebuilds.

• A solid understanding of how records transition from ingestion through processing to a served dataset.

• Direct experience with entity resolution, record linkage, or matching systems.

• Proven, current application of AI to enhance data systems, including integrating an LLM into a production data process.

• Experience in designing evaluations for model output, including golden sets, precision and recall, LLM-as-judge, human-in-the-loop routing, and monitoring production drift.

• Proficiency in coding, including the ability to read a pipeline, write prompts and validators, execute analyses in SQL or Python, and collaborate with engineers.

• Experience working closely with engineering and data science teams on complex, data-intensive systems.

• A history of influencing technical direction without formal authority.

• A strong bias for action and the capability to maintain focus and complete tasks in a fast-paced, ambiguous, and often chaotic environment.

• Exceptional written and verbal communication skills.

• Preferred: experience with contact, person, identity, or B2B company data.

• Preferred: knowledge of GDPR, CCPA, DNC, and international notification regulations.

• Preferred: familiarity with Claude or similar frontier models, agent frameworks, and evaluation harnesses.

• Preferred: background in an AI research lab or an AI-native data company.

🏝️ Benefits

• Comprehensive benefits package.

• Holistic programs focused on mind, body, and lifestyle designed for overall well-being.

• Additional compensation opportunities such as bonuses, commissions, equity, and other benefits may also be offered.