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GetYourGuide is seeking a Project Manager for the Merchandising team to own outcome-driven projects that improve data quality and supplier/traveler-facing content across the platform. This is a data and process-focused role working with structured content (activity attributes, categories, location data) rather than editorial copywriting.
Key Responsibilities:
- Own projects end-to-end: scope, timeline, success metrics, and independent execution (freelancer content batches, supplier data fixes, quality evaluation cycles)
- Define quality standards for your domain: build and validate datasets, set precision/recall targets, monitor for new failure patterns
- Build AI-powered quality checks: configure and orchestrate LLM-based workflows (OpenAI, Anthropic) to replace manual review at scale
- Partner with senior stakeholders to scope ambiguous problems, then execute independently; prioritize by data-backed impact and present solutions with clarity
You'll work with a hybrid schedule (3 days in-office: Mon/Tue/Thu; 2 days optional remote focus time) and have flexibility to work remotely up to 30 days per year globally.
Requirements:
- Proven experience owning projects end-to-end, from fuzzy operational problems to bounded, delivered results
- Hands-on experience configuring and orchestrating AI/LLM tools (OpenAI, Anthropic, or similar APIs) to automate quality checks, build datasets, or replace manual review (no need to have built models from scratch)
- Comfortable with SQL and notebook-based data tools (Databricks or similar) to query and validate data independently
- Data-driven approach to prioritization, success metrics, and hypothesis validation
- Ability to scope work independently with senior stakeholders and resolve alignment issues proactively
- Experience running processes at volume (freelancer operations, quality standards, tooling)
- Clear communicator in written and verbal English
Preferred Qualifications:
- Experience building or fine-tuning LLM prototypes
- Background in content quality, supplier operations, or marketplace quality
- Familiarity with precision/recall frameworks and quality evaluation methods
