Requirements

9+ years of experience in Data Science designing robust end-to-end data workflows, with at least 5 years of experience in forecasting techniques or optimization.
Proven track record owning the data science lifecycle including design, evaluation, deployment, and monitoring of models in production.
Experience setting ML best practices and driving their adoption across multiple squads.
Solid programming skills in Python, Docker, and cloud platforms (AWS or GCP).
Hands-on experience with AI frameworks such as TensorFlow, PyTorch, and with Large Language Models (LLMs).
Ability to build consensus among stakeholders and data scientists, lead without formal authority, and communicate clearly in English to both technical and non-technical audiences.

What you'll be doing

Develop, test, and productionize forecasting algorithms using machine learning, statistical inference, and optimization models.
Act as the technical leader for ML projects in your domain and own their model and architecture design.
Set ML best practices and standards for squads in your domain and drive their adoption.
Review work of data scientists in your domain and provide mentorship.
Collaborate with product and engineering leads to set vision and goals for your squads.
Identify new technologies and opportunities to improve forecasting and operations systems for stakeholders.

Hybrid working model with 2 days a week at the Berlin campus.
27 days holiday plus extra days on the 2nd and 3rd year of service.
Support for career development including a €1,000 educational budget, language courses, parental support, and access to Udemy Business courses.
Health benefits such as health checkups, meditation, and gym access.
Financial benefits including Employee Share Purchase Plan, Sabbatical Bank, public transportation ticket discount, life and accident insurance, and corporate pension plan.
Meal benefits with digital meal and food vouchers.
Relocation support and resources for moving to Berlin.