Senior Product Manager - AI-Driven Competitive Intelligence

Phx Fwd

Phoenix (AZ)

On-site

USD 120,000 - 150,000

Full time

2 days ago

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Job summary

ClearDemand is seeking an experienced Senior Product Manager to lead the Competitive Intelligence product suite. You will own the strategy, roadmap, and end-to-end delivery of data-driven intelligence capabilities for retailers in a fast-paced SaaS environment.

You will drive web scraping, data acquisition, product matching, and DaaS offerings, collaborating with Engineering, Data Science, and UX teams to translate complex capabilities into measurable customer value and scalable products.

Qualifications

7+ years of Product Management experience in B2B SaaS, retail tech, competitive intelligence, or data-driven products.
Experience with web scraping, data acquisition, data quality, scalability, and operational challenges.
Experience with product matching and entity resolution, including taxonomy, fuzzy matching, and ML-based approaches.
Knowledge of Data-as-a-Service (DaaS) models, APIs, and subscription-based intelligence products.
Strong understanding of retail pricing, competitive benchmarking, assortment intelligence, and retailer positioning.
Experience managing data-intensive products involving large-scale processing, automation, analytics, and AI/ML capabilities.
Strong product discovery, requirements, roadmap prioritization, stakeholder management, and agile execution skills.
Ability to translate complex technical capabilities into measurable customer outcomes.
Comfortable operating in fast-paced, ambiguous environments with ownership and bias for action.

Responsibilities

Own the product strategy, roadmap, and end-to-end delivery of Competitive Intelligence capabilities, including pricing, matching, data enrichment, and intelligence delivery.
Drive requirements for web scraping, automated data acquisition, data normalization, and scalable data pipelines.
Define and enhance product matching capabilities, including attribute-based, fuzzy, semantic, and AI/ML-driven approaches.
Develop scalable DaaS offerings with APIs, data feeds, and analytics.
Partner with Engineering, Data Science, UX, and customer-facing teams to drive discovery, prioritization, and execution.
Establish success metrics around data coverage, freshness, matching accuracy, data quality, and adoption.
Balance strategic investments with customer commitments, scalability, and speed to market.