Staff / Principal Data Scientist

Xcede Hannover-braunschweig-göttingen-wolfsburg Region
Relocation
This Job is No Longer Active This position is no longer accepting applications

Job Description


Salary up to €115,000
Location: Braunschweig

One of the largest clothing retailers in Europe is hiring a Staff / Principal Data Scientist to join their growing team. With 1,000+ stores across Europe and Asia and over €4 billion in annual revenue, this brand is combining fashion with cutting-edge data science and they’re looking for someone to lead the way.

The Position:
  • Drive high-impact machine learning use cases across assortment planning, demand forecasting, and markdown optimisation
  • Own complex, business-critical data science projects end-to-end, from stakeholder discovery to deployment
  • Build and deploy predictive models using Python, Spark, and modern ML frameworks (e.g., PyTorch, scikit-learn)
  • Collaborate with data engineering and business teams to develop scalable, production-ready solutions
  • Act as a role model and hands-on contributor, mentoring junior data scientists and reviewing code
  • Present insights to senior stakeholders and influence strategic decision-making
  • Help shape the long-term ML and AI strategy across the retail business
Experience:
  • 7+ years of data science or ML experience, ideally in retail, fashion, or e-commerce
  • Advanced knowledge of Python, SQL, and big data tech like Spark
  • Experience with frameworks like scikit-learn, PyTorch, SparkML
  • Strong communicator, confident presenting to large groups (50–100 stakeholders)
  • Proven experience leading projects and collaborating with cross-functional teams
  • Fluent in German (C1+) and English
  • STEM degree (Master’s or PhD preferred)
Benefits & Details:
  • Up to €115,000 salary
  • Office-based role in modern Braunschweig HQ (relocation support available)
  • 30 days of holiday
  • Generous employee discount on products
  • Structured progression plan and L&D budget
  • Annual capital-forming contributions (e.g., pension, savings)
  • 2-stage interview process
For more information, apply or contact Norman Cistovas.

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