Data Scientist

Roles & Responsibilities

• Experience

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• Minimum of 8 years of experience in AI development, data engineering, or related fields, with at least 5 years focused on GenAI applications.
• Proficiency in Python, with experience in libraries such as Pandas, NumPy, and PyTorch/TensorFlow.

• GenAI Expertise

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• Hands-on experience with Azure OpenAI services and non-OpenAI LLMs.
• Familiarity with LangChain, RAG applications, MCPs and prompt engineering techniques.
• The ability to navigate technology hype, identify and prioritize game-changing applications for our group and execute their development in agile squads
• A deep understanding of foundational and large language models and the vision and hands-on mindset to make your ideas come to life in ZEISS solutions
• Experience with best practices in model development and deployment (Azure Machine Learning Service/ MLflow)
• Experience with fine-tuning and deploying LLMs at scale.

• Data Engineering

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• Strong knowledge of ETL/ELT processes, data pipelines, and workflow orchestration tools
• Experience with connecting to enterprise systems like SAP, cloud databases, and APIs.

• Architecture & Scaling:

• Proven experience in designing and scaling AI systems for enterprise applications.
• Expertise in cloud platforms (Azure preferred, AWS/GCP as a plus) and distributed computing.
• Familiarity with containerization (Docker) and orchestration (CI/CD pipelines and terraform).

• Databases

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• Strong SQL skills and experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cosmos DB).

• Problem-Solving

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• Strong analytical and problem-solving skills with the ability to debug complex systems.

• Communication

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• Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.

• Leadership

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• Proven ability to lead and mentor teams, manage projects, and deliver results.
• Strong communication and stakeholder management skills.