Staff Product Manager (Remote)

Weedmaps is a global leader in the cannabis industry, and they are seeking a Staff Product Manager focused on Personalization. This role involves defining the roadmap for personalization strategies, partnering with ML and AI teams to enhance customer experiences, and leading cross-functional teams to implement these initiatives effectively.

Responsibilities:

• Define a roadmap that achieves a world-class personalization strategy, delivering relevant and tailored experiences across the Weedmaps platform
• Partner with ML and AI teams to build and scale personalization capabilities, including product recommendations, personalized search ranking, and AI-powered features
• Translate business goals and customer needs into a logically sequenced and optimized product roadmap
• Maintain and prioritize a backlog, ensuring new features and enhancements are validated and clearly specified
• Lead a cross-functional team to implement the personalization vision efficiently, aligning stakeholders across product, engineering, data science, and design
• Monitor adoption, engagement, and revenue impact of personalization features and report on release performance as necessary
• Collaborate with product, program, and engineering leaders across the organization to guide the platform roadmap, pinpointing new opportunities for personalization at scale
• Oversee enterprise-level product planning including identifying new personalization opportunities and incorporating a rolling roadmap of business projects and technology initiatives
• Write complete and detail-oriented product requirements documents, ensuring clear communication to business, design, and development teams
• Engage with customers through a variety of channels and serve as the voice of the customer internally, using insights to inform personalization strategy

Requirements:

• Bachelor's degree or equivalent work experience
• 8+ years of product management experience in a technological industry
• Proven track record of operating at a staff or principal level, driving product strategy across multiple teams or domains
• Deep data background using self-service analytics tooling (Mixpanel, Amplitude, Heap, etc.)
• Experience working with ML/AI teams to build and ship personalization systems, recommendation engines, or intelligent ranking models
• 4+ years experience in consumer-facing online commerce, point-of-sale, or marketplace environments
• 2+ years experience owning a personalization, search, or ML-powered product stack at scale
• Demonstrated ability to influence senior leadership and drive org-wide alignment on complex, ambiguous problems
• Strong strategic aptitude with a proven ability to define a winning product vision and roadmap, particularly in personalization, recommendations, or AI-powered product domains
• Deep customer empathy and experience intuition; demonstrated success building tailored, intelligent user experiences that drive engagement and retention
• Excellent communication and persuasion skills; proven ability to build executive buy-in for bold, long-term bets in emerging AI/ML product spaces
• Strong analytical and quantitative skills with a bias toward data-driven decision making, including comfort with A/B testing, experimentation frameworks, and ML model evaluation
• Ability to translate personalization strategy into detailed, actionable product requirements that bridge business goals and ML/AI capabilities
• High technical fluency; comfortable engaging deeply with ML engineers and data scientists on model tradeoffs, feature pipelines, data infrastructure, and system architecture
• Proven ability to navigate build vs. buy vs. partner decisions for AI/ML capabilities, balancing customer impact with speed to market
• Comfortable operating in ambiguity; able to define structure and drive progress on complex, cross-functional initiatives without a clear playbook
• Strong bias for action with the ability to manage competing priorities across multiple teams in a fast-paced, high-growth environment
• Proven ability to lead and align cross-functional teams — including engineering, data science, design, and marketing — through influence rather than direct authority
• Familiarity with modern AI/ML development workflows, including experience working in agile environments with data science and ML engineering teams