Product Manager - AI
New
I
Infatica.ioSocial analytics
Workable workplace: remote Workable remote: True Workable locations: Spain Location: SpainFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- Several years in product management
- Required Skills
- Product ManagementProduct AnalyticsRESTful APIsWritten communicationSaaSA/B testing
Requirements
- Several years in product management, preferably with early-stage B2C, prosumer SaaS, creator/social, analytics, martech, or intelligence products.
- Proven experience launching MVPs or new product features from zero, with clear hypotheses, metrics, user feedback loops, and post-launch decisions.
- Strong product analytics skills: event taxonomy, funnel analysis, cohorts, A/B testing, activation/retention metrics, and tracking requirements.
- Ability to manage several product tracks or experiments without losing clarity on priorities, owners, decisions, and business impact.
- Technical understanding strong enough to discuss APIs, data ingestion, tracking events, AI/LLM limitations, data quality, latency, edge cases, and implementation trade-offs.
- Experience working with remote, distributed, or outsourced engineering teams.
- Excellent written communication: clear PRDs, decision notes, experiment summaries, and stakeholder updates.
- High ownership, high autonomy, and comfort working in ambiguity without waiting for perfect inputs
Responsibilities
- 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
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