Candidate Profile Skills & Competencies:
- 3-6 years of experience in Product Management, with proven ownership of consumer-facing (B2C) products.
- Hands-on experience building or driving adoption of AI/automation-powered product features (LLMs, ML models, RAG pipelines, OCR automation, chatbots, recommendation engines, etc.).
- Strong grasp of product metrics and funnel thinking comfortable citing real numbers (conversion lift, CAC reduction, retention improvement) tied to your work.
- Excellent communication and stakeholder management skills ability to work cross-functionally with engineering, design, data, and business teams.
- Strong analytical skills comfortable with Excel, SQL, and analytics platforms (Mixpanel, Amplitude, or similar) for data-driven decision-making.
- High ownership, adaptability, and ability to thrive in a fast-paced, high-growth environment.
Key Responsibilities:
Product Ownership:
- Own the end-to-end product lifecycle for a consumer-facing product area from discovery and problem definition to roadmap, execution, and post-launch iteration.
Roadmap & Prioritization:
- Translate user research, behavioral data, and business goals into a clear, prioritized product roadmap.
AI & Automation:
- Identify opportunities to apply AI/automation LLMs, ML models, RAG, OCR to reduce manual effort, improve product experience, or unlock new capabilities.
AI Feature Delivery:
- Own end-to-end delivery for at least one AI-powered or automated feature, from idea to adoption, partnering closely with engineering and data teams.
Metrics & Experimentation:
- Define and track success metrics for every feature shipped; run experiments (A/B tests, funnel analysis) to validate impact.
Customer Focus:
- Deeply understand the end consumer through user interviews, support tickets, analytics, and market research; represent their voice in every decision.
Stakeholder Communication:
- Communicate roadmap, outcomes, and trade-offs clearly to stakeholders and leadership.
Data & Insights:
- Track product and funnel metrics (activation, retention, conversion, CAC/LTV, etc.) and derive actionable insights to improve the product experience.
Cross-functional Collaboration:
- Work closely with Engineering, Design, Data, and Business/Growth teams to ship and scale features end-to-end.
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