Job Description
We are on the lookout for a Data Scientist to join our GlobalRanking and Recommendations domain and help us enhance our user experience and with that help our customers easily discover new products and vendors. If you’re a creative problem solver who is hungry for a new adventure, an international workplace is waiting for you in the heart of Berlin!
At Delivery Hero, you’ll shape the global consumer experience for millions of users. Your work will have a direct impact on how we attract and retain customers, creating data-driven, personalized interactions that keep them coming back. As part of our Consumer Team, you’ll enhance customer satisfaction and drive global growth and profitability through innovative projects.
1. Deep dive into our data to generate insights about our customers, our products and our existing recommendation techniques.
2. Develop new data products from conception to production to help optimize our recommendation systems and improve the experience for our customers.
3. Transform fuzzy/high-level requirements and objectives to solvable problem statements and requirements
4. Collaborate with Senior Data Scientists, Product Specialists, and user experience squads to understand business processes, identify data and solution requirements.
5. Work with Data Engineers / MLOps to optimize and deploy your models.
6. Scale up your algorithm to provide business value in dozens of countries globally supporting multiple brands and millions of customers.
7. Help defining data needs to further improve existing algorithms.
8. Work with structured and semi-structured data from different data sources (BigQuery, PostgreSQL etc and many more).
9. Contribute and make an impact in a global, fast-moving tech organization.
Qualifications
10. You have at least 3 years of experience applying methods from Machine Learning and Statistics to real-world datasets.
11. You excel at modeling business problems using machine learning techniques covering feature engineering, model selection and design as well as evaluation and optimisation to deliver value to the business.
12. You can write maintainable code that follows best practices in Software Engineering and effectively software versioning with Git.
13. You are eager to put your models to production to get real customer feedback as soon as possible.
14. You have the ability to understand a business problem and translate, structure it into a data science problem.
15. Fluency in Python and familiarity with its scientific stack such as numpy, pandas, scikit-learn, matplotlib.
16. You have previous experience building recommendation or ranking systems.
17. You have experience with experimentation with different approaches through an AB testing methodology and offline evaluation
18. You know how to write a SQL query to pull the data you need.
19. Fluency in English.
Nice to have:
20. You have experience solving problems related to offline evaluation and monitoring recommendation & ranking systems.
21. Experience deploying complex models to serve live traffic and collaborating with ML engineers in creating efficient systems that integrate ML models following good MLOps practices.
22. Practical experience and knowledge of Deep Learning models & NLP techniques.
23. You know how to make your code run in a container and are enthusiastic about running it in modern infrastructure environments like Kubernetes.
24. Knowledge of GCP and cloud in general.