Team Lead Data Science (all genders)

Holidu is one of the world’s 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 lead a group of four Data Scientists, embedded in three cross-functional product squads (including Ranking/Search and Revenue Management).
• You’ll collaborate daily with Data Engineers, Analysts, Product Managers, and Engineers.
• You’ll report to the Director of Business Intelligence.

About BI at Holidu

Our Business Intelligence department is a multidisciplinary team of analysts, data scientists, and data engineers, plus a central BI platform team. Together, we ship ML features that directly move GMV, conversion, and retention.

Our Tech Stack

• Python
• Airflow
• dbt
• AWS (SageMaker, Redshift, Athena)
• MLflow

Your role in this journey

You and your team\’s mission is to deliver reliable, measurable business impact through applied machine learning. You will:

• Ship high-impact ML features across ranking, recommendations, retention, and revenue management, driving GMV, conversion, churn reduction, and feature adoption.
• Accelerate experimentation and decision quality measured by number of successful A/B tests per quarter, time-to-decision, and experiment coverage of key hypotheses.
• Ensure model reliability in production measured by online/offline agreement, model & data drift KPIs, latency & uptime SLAs, and automated monitoring coverage.
• Advance our MLOps practices with CI/CD pipelines, retraining workflows, lineage tracking, and documentation. Measured by percentage of models with automated pipelines, mean time to restore after regressions, and incident rate.
• Grow and mentor your team and increase engagement by coaching, hiring, and supporting their professional development. Measured by eNPS/engagement signals, hiring success, internal promotions, and mentoring outcomes.
• Drive cross-team alignment with Product, Engineering, and GTM functions. Measured by on-time delivery to roadmap milestones and stakeholder satisfaction.

What’s already in production: Booking cancellation prediction, churn prediction, contextual ranking, reinforcement-learning ranking, property recommendations, time-series forecasts, and causal inference models. You’ll own the roadmap and quality bar for these and lead the next generation of ML applications at Holidu.

Your backpack is filled with

• Applied ML leadership: Proven track record leading Data Science in product settings; you’ve shipped ML models that improved key business metrics in production.
• Depth in problem space: Experience in ranking/recommendation systems, time-series forecasting, causal inference & experimentation, supervised and unsupervised learning on tabular data, and ideally reinforcement learning/bandits.
• Excellent analytical skills: Statistics, experimental design, and inference – you know how to frame problems and measure impact.
• Modern ML & Data Stack expertise: Python, SQL, and production workflows with Airflow, dbt, MLflow, and AWS (SageMaker, Redshift, Athena). Familiarity with CI/CD and observability for ML systems.
• Product intuition & stakeholder management: You can explain complex models in simple terms, influence product direction, and align across engineering, product, and business partners.
• Strong project management skills , including the ability to track and plan large, multi-month projects with clear milestones.
• AI Proficiency: You are comfortable using AI to enhance coding, planning, and monitoring. This includes successfully integrating AI tools into their workflow and being able to teach others how to use these tools efficiently.
• People leadership: Coaching, feedback, and hiring skills that raise the bar for a multi-team Data Science group.

Our adventure includes

• Impact: Shape the future of travel with products used by millions of guests and thousands of hosts. Ideas become products, data drives decisions, and iteration fuels fast learning. Your work matters and you’ll see the impact.
• Learning: Grow professionally in a culture that thrives on curiosity and feedback. You’ll learn from outstanding colleagues, collaborate across disciplines, and benefit from mentorship and personal learning budgets with a strong focus on AI.
• Great People: Join a team of smart, motivated and international colleagues who challenge and support each other. We celebrate wins and keep our culture fun, ambitious and human. Our customers are guests and hosts—people you can relate to, making work meaningful and energizing.
• Technology: Work in a modern tech environment. You’ll experience the pace of a scale-up combined with the stability of a proven business model, enabling you to build, test, and improve continuously.
• Flexibility: Work a hybrid setup with 50% in-office time for collaboration, and spend up to 8 weeks a year from other inspiring locations. You’ll stay connected through regular events and meet-ups across our almost 30 offices.
• Perks on Top: Travel benefits, gym discounts, and other perks to keep you energized — but what truly sets us apart is the chance to grow in a dynamic industry, alongside amazing people, while having fun along the way.

Want to travel with us?

Apply online on our careers page. Your first travel contact will be Katharina from HR. We are committed to diversity in all aspects of our business. We encourage applications from all genders, all corners of the world and all individual backgrounds. You are welcome to submit your application without a photo and without stating your gender, date of birth, marital status, nationality or disability status (if applicable). If you require any special assistance when arranging interviews, office visits or the recruitment process in general, please contact the relevant HR person responsible for this job and we will do our best to accommodate your needs.

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