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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in end-to-end dataset management, including sourcing, development, and commercialization, while effectively collaborating with engineering teams and strategic customers. Proficient in SQL and AI tooling, with a strong understanding of entity resolution and data quality standards.
Highest-signal resume keywords
Dataset ManagementSQL ProficiencyEnterprise Product ManagementData Solutions DevelopmentCustomer-Facing Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLEntity ResolutionData Solutions DevelopmentPricing ModelsData Quality Standards
Soft Skills
Commercial MindsetOwnershipUrgency
Tools & Technologies
AI ToolingClaude Code
Industry Keywords
B2B DataData LicensingData-as-a-ServiceFinancial ServicesInsurance
Tech Stack
Tools & technologiesSQL
About the role
Key responsibilities & impact- Own vertical datasets end to end, including sourcing, development, entity resolution, delivery, pricing, packaging, and revenue generation
- Define dataset audiences, coverage, accuracy, quality standards, and completion criteria
- Partner with data engineering and platform engineering to deliver datasets from the warehouse to the GTM Data Store, APIs, MCP, and applications
- Write requirements, define use-case queries, own testing, and drive handoffs
- Own pricing and packaging, including price-book placement, licensing models, supplemental terms, and bundling
- Enable product-led and sales-led commercialization through in-product discoverability, sales materials, data reference guides, use cases, positioning, and sales support
- Work directly with strategic customers and sales teams to understand needs and shape datasets and offers
- Build vertical solutions and workflows by packaging datasets together
- Coordinate data quality, engineering delivery, pricing, legal terms, and marketing across teams
- Prioritize dataset investment based on revenue potential, customer demand, and core-data value
- Feed customer and delivery learnings back into future product development
Requirements
What you’ll need- Commercially minded; understands products in terms of who pays and why
- Experience owning a number or working closely enough with one to influence prioritization
- Heavy customer-facing background in enterprise product management, solutions consulting, professional services, or a customer-facing data-company role
- Experience building data solutions from multiple datasets into products or workflows for specific markets
- Experience ideally in financial services, insurance, or another data-heavy vertical
- Broad product management experience spanning discovery, requirements, engineering collaboration, launch, enablement, pricing, and shipping across multiple teams
- Proficiency with SQL
- Understanding of entity resolution and tradeoffs between coverage, accuracy, and freshness
- Experience with B2B data, data licensing, or data-as-a-service is a strong plus
- Experience with public records, regulatory filings, or vertical-specific data sources is a plus
- Ownership and urgency
- Proficiency with AI tooling, including Claude Code or similar tools
Benefits
Comp & perks- Comprehensive benefits
- Holistic mind, body and lifestyle programs designed for overall well-being
- Additional compensation may include bonus, commission, and equity