Job Description
We are on the lookout for a Staff Data Scientist to join our Quick Commerce Commercial Tribe. In this role you will be exposed to various topics related to our Quick Commerce business – assortment optimisation, content generation, promotion effectiveness improvement, and ranking. You will help other Data Scientists to deliver high quality solutions, challenge our assumptions and improve DS practices across our teams.
As a Staff Data Scientist, you will work closely with multiple cross-functional teams (Data Scientists, Machine Learning Engineers, and Software Engineers) to build and maintain highly scalable and reliable ML services deployed in dozens of countries globally with millions of customers.
If you're a skilled Data Scientist and creative problem solver who is eager to deliver solutions and hungry for a new adventure, an international workplace is waiting for you in the heart of Berlin!
1. Guide the discovery of new innovative data products from conception to operationalization to help optimize our systems and improve the experience for our users.
2. Keep yourself up to date and suggest state-of-the-art models to find out what works best for our customers.
3. Be the main reference point for new research and tech quality of Data Science in Qcommerce Commercial & Media Solutions tribes.
4. Enable collaboration and knowledge sharing by pushing cross teams’ projects.
5. Set up our teams for success by creating a long-term vision, a mid-term strategy, and several short-term roadmaps toward some of the most complex and interesting data problems.
6. Last but not least, you are not afraid to build global systems that are used by thousands of people and constantly strive for excellence.
Qualifications
7. Sound statistical skills – you need to be very comfortable with fundamentals and first-principles thinking when it comes to statistics & machine learning theory.
8. Strong engineering fundamentals – you write maintainable code in Python that follows best practices in software engineering. You hold yourself and others to a high bar when working with production systems (observability, monitoring, performance).
9. Deep expertise in at least one relevant domain ( causal inference, time series, Bayesian methods, neural networks, NLP/LLM, ranking/matching, advanced experimentation)
10. Before starting to work on a use case, you carefully question existing assumptions and care a lot about clean data.
11. You are a good communicator and are able to filter down requirements coming from many stakeholders to the ones that make an MVP.
12. You care about agile software processes, data-focused development, reliability, and disciplined experimentation.
13. You have experience mentoring other team members.
Nice to have:
14. Demonstrated leadership abilities in an engineering environment in driving operational excellence and best practices.
15. Experience in designing and implementing large scalable distributed systems with micro-services and heterogeneous platform components.
16. Knowledge of GCP.
17. Proven records of knowledge sharing activities like presenting in conferences or publications.
18. You know about A/B testing and are able to discern signals from noise when it comes to estimating the effect of new models.