Define and evolve the Intelligence Catalog’s taxonomy, metadata structures, detection labels, enrichment signals, and classification schemas.
Manage how intelligence is created, governed, evaluated, refreshed, and retired.
Drive noise-reduction methodologies and precision/recall improvements across all catalog intelligence.
Partner with Applied ML to define evaluation frameworks, labeling strategies, annotation workflows, and model governance standards.
Ensure catalog intelligence is consistently delivered across Smarsh’s product suite.
Develop a scalable intake process for new intelligence requests, use cases, and customer-driven requirements.
Build and optimize a scalable delivery process ensuring intelligence availability, versioning, and rollout across product teams.
Ensure required services (classification, enrichment, detection, scoring, metadata exposure, etc.) exist and are aligned with catalog needs — collaborating with platform and engineering owners.
Drive creation of a unified intelligence experience across Smarsh’s product portfolio.
Lead customer partnership programs to co-develop new intelligence patterns, detection strategies, and GenAI review experiences.
Gather deep feedback from lighthouse customers to drive roadmap priorities, quality improvements, and new use cases.
Work closely with Customer Success and Product teams to understand performance gaps and opportunities for precision/recall improvements.
Define and own catalog KPIs including precision/recall, noise reduction, signal quality, and MTTR for new intelligence delivery.
Champion responsible AI and model governance practices for catalog-supported intelligence.
Establish processes for versioning, auditability, explainability, and risk management of catalog intelligence.
Serve as the intelligence product expert for internal teams — Product, Engineering, Applied ML, Legal, Compliance, InfoSec, and Customer Success.
Drive alignment on firm-wide intelligence priorities, ensuring the right models and signals are being developed and iterated.
Partner with product teams to ensure catalog intelligence is integrated effectively into customer-facing workflows.
Requirements
5+ years of Product Management experience, including ownership of a data, AI/ML, intelligence, or platform product.
Strong understanding of AI/ML fundamentals, including model evaluation, labeling, annotation strategies, and how to apply precision/recall tradeoffs.
Experience working with Data Science or Applied ML teams as core partners.
Excellent communication skills — able to articulate complex technical concepts to cross-functional teams.
Proven ability to work with internal product teams to drive adoption of shared capabilities.
Highly organized, detail-oriented, and able to manage multiple streams of work simultaneously.
Strong Pluses
Experience in Compliance, Surveillance, Legal, InfoSec, or Financial Crime domains.
Experience with model governance or model risk management frameworks.
Experience in enterprise SaaS environments, especially in regulated industries.
Experience driving noise reduction or precision/recall optimization initiatives.Data Science or Quantitative background