Holidu is one of the worlds fastest-growing vacation rental technology companies. Our mission is to make booking and hosting holiday homes free of doubt and full of joy, by helping hosts generate more bookings with less work and helping guests find a holiday home they truly enjoy. Our team of 700 colleagues from 60+ nations shares a passion for tech, an ambition for constant improvement, and a relentless drive to bring the best experience to more than 40k vacation rental hosts and 4 million annual guests.
Your future team
You'll be part of our new Dynamic Pricing & Revenue Management team, working alongside a Data Scientist and Data Engineer. Together, you will work towards one core goal: helping hosts improve occupancy and earnings through a smart, dynamic and data driven pricing strategy.
You'll work with a large and rich dataset, modern tooling, and teammates who care deeply about impact, collaboration, and learning together.
Your role in this journey
As a Data Analyst, you'll turn complex pricing data into clarity, structure, and actionable insights that guide product and business decisions. You will:
- Act as an analytics partner for Revenue Management, supporting strategic pricing initiatives with clear, data-driven insights.
- Analyze the status quo of pricing performance, adoption, and impact (e.g. weekend pricing, discounts, experiments).
- Build and maintain dashboards and reporting frameworks to track product performance, host acceptance, and revenue impact.
- Conduct deep dives and ad-hoc analyses to test hypotheses and support decision-making.
- Design and create high-quality analytical datasets by combining multiple data sources for pricing and forecasting use cases.
- Collaborate closely with Data Scientists and Data Engineers to prepare training datasets and features for pricing and forecasting models.
- Continuously improve data quality, definitions, and analytical standards within Revenue Management.
Your backpack is filled with
- 3+ years of experience as a Data Analyst in a data-driven environment.
- Strong hands-on expertise in SQL and Python (or similar), with experience working on large, complex datasets.
- Proven experience delivering end-to-end analytics: from data modelling and preparation to insights and stakeholder communication.
- A strong ownership mindset: you proactively identify opportunities, drive analyses forward, and follow topics through to impact.
- The ability to translate complex problems into clear, actionable insights for technical and non-technical audiences.