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 passionate data scientists, is responsible for all topics related to data science and machine learning.

In this internship, you will be embedded in one of our cross-functional teams and work directly alongside experienced data scientists on Data Science projects to generate business impact. You will be exposed to various topics such as rankings, recommendations, user segmentation, user lifetime value, business forecasts, and more.

• Duration: 6 months.
• Location: Munich, 2-3 days office days per week.

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

In this internship, you will take an active part in projects that have direct impact on business outcomes such as guest conversion, host revenue, and marketing efficiency. You will be supported and mentored by experienced data scientists, and have the opportunity to learn from a diverse team across Data Science, Analytics, and Engineering.

You will

• Support the development of machine learning models (e.g. forecasting, churn prediction, recommendation systems, segmentation) using Python and SQL.

• Explore, clean, and transform large datasets within our AWS environment (Redshift, Athena, S3)

• Conduct exploratory data analysis (EDA) to uncover patterns and generate hypotheses.

• Help evaluate model performance and interpret results in a business context.

• Collaborate closely with teams such as Product, Marketing, and Revenue Management to understand their challenges and translate them into data science use cases.

• Participate in team rituals, knowledge sharing sessions, and contribute your own ideas and perspectives to the team's ways of working and best practices.

• Use AI tools to automate repetitive tasks and improve your workflow efficiency.

Your backpack is filled with

• Currently enrolled or recently completed a Bachelor’s or Master’s degree in a quantitative field (e.g. Data Science, Computer Science, Mathematics, Statistics or similar)

• Solid understanding of Python and SQL.

• Foundational knowledge of statistics and machine learning concepts (e.g. regression, classification, evaluation metrics).

• Strong analytical and problem-solving skills, with attention to detail.

• A proactive mindset and eagerness to learn in a fast-paced environment.

Our adventure includes

• Compensation: Get a fair salary.

• Impact: Make a difference for hundreds of thousands of monthly users.

• Growth: Take responsibility from day one and develop through regular feedback.

• Community: Engage with international, diverse, yet like-minded colleagues through regular events and 2 office days per week with your team.

• Flexibility: Benefit from our hybrid work policy and the chance to work from other local offices for up to 8 weeks a year.

• Fitness: Get a corporate Urban Sports Club subscription or a premium gym membership at a discounted rate.

Need a sneak peek?

• Check out the adventure that awaits you on Instagram @lifeatholidu.

• See also what Life as an intern looks like at Holidu.**

**

Want to travel with us?

Apply online on our career page! Your first travel contact will be Lucia from HR.

In addition to your CV, please also upload your recent transcript of records from your university.

*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.*

CONTACT_PERSON

LUCIA

Location

Munich, Germany