2 ΡΠ°ΡΠ° Π½Π°Π·Π°Π΄
Product Manager, Data Products (AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Product Manager, Data Products (AI): Owning and scaling Data-as-a-Service products that enrich first-party records and deliver consumer intelligence through data shares, clean rooms, APIs, marketplaces, and integrations with an accent on product strategy, AI/ML applications, pricing, privacy, and distribution. Focus on translating data capabilities into roadmaps, managing agile engineering delivery, navigating regulated data constraints, and measuring launch performance to guide investment decisions.
Location: United States; remote-first with occasional travel for company and client events
Requirements
- 5+ years of product management or product ownership experience in data products, martech, or adtech.
- Experience taking products from requirements through launch and adoption, including data enrichment or appends against first-party records.
- Experience with large-scale data delivery through file transfer, data sharing, clean rooms, or APIs.
- Working knowledge of AI/ML workflows, technologies, and architectures, plus identity resolution and consumer data ecosystems.
- Familiarity with licensed consumer data privacy, state privacy laws, opt-out handling, and regulated categories.
- Fluency in agile product delivery, backlog management, sprint ceremonies, Jira, and writing product specifications and vision documents.
Nice to have
- Experience with data marketplaces, self-service trials, pricing and packaging for data products, or audience activation in paid channels.
- Hands-on experience with AWS, Snowflake, Databricks, or clean room environments.
- Experience in regulated verticals, especially financial services.
- Familiarity with agentic frameworks and MCP server-based data access.
What you will do
- Own the vision, roadmap, business case, success metrics, and lifecycle of products in the Data-as-a-Service suite.
- Translate product strategy into requirements and user stories while managing the backlog, refinement sessions, and sprint ceremonies with engineering.
- Work with data science and engineering to apply AI and machine learning while evaluating technical and product trade-offs.
- Own pricing, packaging, and distribution through data marketplaces, self-service trials, partner integrations, and MarTech channels.
- Partner with Legal and Engineering to ensure compliant delivery of licensed data, including opt-out handling and regulated-category constraints.
- Bring products to market with Marketing, Sales, and Customer Success, then track launch performance and guide future investment decisions.
Culture & Benefits
- Remote-first work environment with flexible collaboration across locations and intentional in-person collaboration when needed.
- Opportunity to work on AI-powered marketing data and identity products used by enterprise customers.
- Competitive 401(k) match and an Open PTO policy.
- Comprehensive benefits package for employees and their families.
- Company headquartered in Reston, Virginia, with offices in New York City and Washington, D.C.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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