About the role
Explore a new world of possibilities HomeToGo is Europe’s leading vacation rental group with the vision of unlocking better stays. Our team is united by a passion for travel, driven by innovation and impact, and guided by open-minded leaders at every level. Our commitment to recognizing and empowering exceptional talent is the foundation of our growth. We are actively hiring candidates from all around the world, including sponsoring visas for Germany. An amazing journey of opportunity with an international team lies ahead - join us! Your future contribution Every search result, every listing page, every booking on HomeToGo starts with the data layer you'll own. We aggregate 15M+ accommodations from over 1,000 supply partners, and someone needs to make sure that catalog is accurate, deduplicated, enriched, and ready for whatever surface comes next — classic search, AI-powered discovery, or channels that don't exist yet. You'll be the single product owner for marketplace data infrastructure: a hands-on, individual-contributor role that sits at the intersection of product, data science, and engineering. You get a dedicated engineering squad, close partners in Data Science and ML Engineering, and a direct line to the Managing Director of HomeToGo Marketplace. The Berlin-based seat comes with real leverage — your decisions ripple across every surface of the product. This is not a front-end consumer role. It's the kind of work where getting deduplication right lifts conversion across the entire marketplace, where a better quality score reshapes what millions of travelers see first, and where the data you structure today determines whether we show up in tomorrow's AI platforms. You'll define the roadmap yourself. Here's where the value sits from day one: Make our matching and merge system best-in-class. We deduplicate across 1,000+ partners using ML. You'll own the product direction: precision vs. recall trade-offs, object and unit modeling, and the feedback loops that make the system smarter over time. Getting this right lifts listing quality and booking conversion in one move. Define what "good data" means, then enforce it. Build and evolve the quality scoring framework that tells us — and our partners — how complete, accurate, and competitive every listing is. You set the bar for the entire catalog. Get our inventory ready for AI distribution. LLM platforms, conversational search, structured data for generative AI — the accommodation data needs to surface cleanly in all of them. You'll shape what discoverability means in a post-search world. Enrich what we have. Image embeddings, content enrichment, format migrations — the work that turns raw partner feeds into listings travelers actually want to book. You won't do all of this in your first quarter, but you'll decide the order, defend the bets with evidence, and own the numbers either way. How you’ll add value Run marketplace data infrastructure like your own business: own the bets, the trade-offs, and the results Decide what we build, what we kill, and what we never start, and defend those calls with data Collaborate deeply with Data Science and ML Engineering on production systems — you don't build the models, but you evaluate them, define metrics, and challenge assumptions Translate infrastructure wins into language that C-level stakeholders care about, and present regularly to senior leadership Work across Search & Discovery, Partner Integrations, and Commercial teams to turn data improvements into user-facing impact Track AI development closely and think ahead about how our data layer needs to evolve You’ll be successful in this role if you Have owned data-intensive or infrastructure products and can show the impact in numbers (conversion, revenue, efficiency, data quality) Bring solid product management experience with at least 2 years in a senior or lead PM role Know marketplace dynamics deeply — multi-provider data aggregation, two-sided platform challenges, the messiness of real-world supply data Have worked hands-on with Data Science or ML Engineering on production ML systems (matching, classification, NLP, or similar) Are comfortable with SQL and modern data tools (Snowflake, BigQuery, Superset, or equivalent) — you challenge assumptions with queries, not gut feel Understand A/B testing methodology end to end: hypothesis, statistical significance, interpretation Communicate complex technical concepts clearly to non-technical stakeholders Are fluent in English Even better if you Thrive in a high-leverage seat where your work touches every surface of the product Get energy from making invisible infrastructure visible through its downstream impact Move comfortably between ML model evaluation, partner data quality conversations, and C-level strategy presentations See AI distribution as a product problem, not just a technical one Have experience in travel, accommodation, or e-commerce marketplaces Know accommodation data structures (property types, room types, rate plans, availability feeds) Understand structured data, schema.org, and discoverability principles Have built with AI-assisted tools yourself (Cursor, Claude Code, Gemini, GitHub Copilot) Bring API design or partner integration experience Come from or have crossed over from business development, operations, or commercial roles — understanding the supply side of a marketplace is a major asset What we offer AI-first culture: Leverage a world-class AI ecosystem with Google Enterprise+, Slack AI, and SOTA model access via Copilot, Claude or LiteLLM. By using our custom agents for automation and knowledge management, you’ll become a first-class adopter of the AI workflows defining industry best practices. Flexible hybrid work: Work remotely up to 50% of the year, including up to 63 days of "work from anywhere" within the EU and UK.* Competitive
