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 will be part of the Business Intelligence department, which consists of the Data Science, Data Analytics, and Data Engineering teams. The Data Science team, composed of other experienced and passionate data scientists, is responsible for everything related to data science and machine learning. You will be working on various topics such as rankings, recommendations, user segmentation, user lifetime value, business forecasts, etc. You will have access to our huge dataset and work in collaboration with stakeholders from various departments. Your objective is to build the best internal and external products for our customers. Holidu highly values a diverse and open environment with people from all over the world. This role is based in Munich with a hybrid setup.
Our Tech Stack
- Flexible data science environment (Python, SageMaker)
- Database: AWS stack (Redshift, Athena, Glue, S3)
- Data pipelines: Airflow, dbt
- Data visualization: Looker
- Data analytics: SQL, Python
- Collaboration: Git
Your role in this journey
- Collaborate across various business departments to identify opportunities and solve critical business challenges using data science solutions.
- Build and optimize predictive models such as booking cancellation forecasts, churn predictions, pricing optimization, revenue forecasting and marketing channel allocation.
- Take models from conception to production, continuously monitor their performance, and iterate to enhance accuracy and efficiency.
- Interface with diverse business stakeholders, ensuring alignment between data science initiatives and company goals.
- Demonstrate leadership in data science projects, leveraging your expertise to drive measurable business impact.
Your backpack is filled with
- A degree in machine learning, computer science, mathematics, physics, or a related field.
- Expertise in statistics, predictive analytics, machine learning techniques, and proficiency in tools like Python and SQL.
- Experience with Airflow and dbt is a plus.
- Strong understanding of business operations and experience collaborating with diverse stakeholders.
- Enthusiasm for data science and a drive to deliver world‑class products that make a difference.
We welcome candidates at all career stages. We value potential and a willingness to learn over deep prior experience.
Our adventure includes
- Impact: Shape the future of travel with products used by millions of guests and thousands of hosts.
- Learning: Grow professionally in a culture that thrives on curiosity and feedback.
- Great people: Join a team of smart, motivated, and international colleagues who challenge and support each other.
- Technology: Work in a modern tech environment.
- Flexibility: Work a hybrid setup with 50% in‑office time and up to 8 weeks a year from inspiring locations.
- Perks on top: Travel benefits, gym discounts, and other perks to keep you energized.
Want to travel with us?
Apply online on our careers page! Your first travel contact will be Lucia 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.
Location
Munich, Germany
