- Own the product lifecycle from opportunity discovery, problem framing, MVP definition, launch, analytics, iteration, and scale.
- Translate business goals and user problems into clear product hypotheses, scope, metrics, event tracking, user stories, and acceptance criteria.
- Build, test, and iterate MVPs rapidly using user feedback, funnel data, cohort behavior, competitive signals, and AI-assisted research.
- Define product vision, product strategy, success metrics, and prioritization logic for one or more product streams.
- Set up or specify product analytics: events, funnels, cohorts, activation metrics, retention metrics, experiment logic, and reporting needs.
- Work closely with engineering, design, marketing, sales, support, and leadership across a remote/distributed setup.
- Manage collaboration with outsourced and remote development teams, keeping scope, quality, timelines, and product decisions transparent.
- Use AI tools as part of daily product operations: discovery synthesis, competitor monitoring, PRD drafting, analytics exploration, QA support, prototype ideation, and productivity automation
Product ManagementProduct AnalyticsRESTful APIs+3 more