Data Scientist (AI & Decision Intelligence) - All genders
This job is at Lufthansa Group. You apply to them, not to GoAusbildung.
Start Date
On request
Sector
IT / Data Science / Aviation
Salary
Competitive salary
Listing data as of November 1, 2026
About this Apprenticeship
EWH is looking for an AI enabled Data Scientist combining strong analytical expertise, software engineering discipline, business understanding, and AI productivity skills. Design, build, and deploy Machine Learning and AI solutions from idea to production. Develop forecasting, recommendation, pricing, customer segmentation, and optimization models. Leverage GenAI and LLM technologies to automate processes and enhance business decision-making. Partner with stakeholders across Commercial, CRM, Finance, Operations, and Product teams. Transform ambiguous business questions into analytical frameworks and actionable insights. Build scalable solutions using cloud technologies and modern data platforms. Evaluate AI opportunities and determine where classical ML, optimization, or GenAI delivers the highest value.
What You'll Learn
- Design, build, and deploy Machine Learning and AI solutions from idea to production.
- Develop forecasting, recommendation, pricing, customer segmentation, and optimization models.
- Leverage GenAI and LLM technologies to automate processes and enhance business decision-making.
- Partner with stakeholders across Commercial, CRM, Finance, Operations, and Product teams.
- Transform ambiguous business questions into analytical frameworks and actionable insights.
- Build scalable solutions using cloud technologies and modern data platforms.
- Evaluate AI opportunities and determine where classical ML, optimization, or GenAI delivers the highest value.
Requirements
- 5+ years of Data Science experience.
- Strong Python or R.
- Experience with Machine Learning and Statistics.
- Experience with cloud platforms (Azure, Databricks).
- Experience deploying models into production.
- Strong experimentation and causal inference knowledge.
- Data engineering understanding (pipelines, APIs, orchestration).
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