Senior Data Scientist (Applied AI / LLM)

The role

Nebius is looking for a Senior Data Scientist (Applied AI / LLM) to design, build, and deploy production-grade AI systems based on large language models. You will focus on turning LLM capabilities into reliable, measurable business solutions, while also contributing to predictive modeling across different business domains.

Your work will include building evaluation frameworks, improving model accuracy, and developing agent-based systems that automate analytical and data workflows (e.g., data quality monitoring). The role emphasizes production readiness, robustness, and real business impact—not experimentation.

You’re welcome to work in our office in Tel Aviv.

Your responsibilities will include: 

• LLM system development. Design and deploy LLM-based solutions (e.g., RAG pipelines, agent workflows) for real business use cases.
• Evaluation & reliability. Build evaluation frameworks to measure accuracy, consistency, and failure modes of LLM systems. Continuously improve performance based on real-world usage.
• Agent-based automation. Develop agentic solutions to automate workflows such as data quality checks, anomaly detection, and reporting.
• Applied predictive modeling. Apply classical ML and statistical methods to business domains such as HR and Finance (e.g., forecasting, classification, risk modeling).
• Production & MLOps. Deploy and maintain models in production, ensuring monitoring, versioning, and scalability.
• Stakeholder collaboration. Translate business needs into AI/ML solutions and communicate trade-offs, risks, and performance clearly.
• Cross-domain contribution. Contribute to adjacent areas (e.g., forecasting models) to ensure team redundancy and shared ownership of critical workflows.

We expect you to have: 

• Experience as a data scientist or applied ML practitioner (5+ years).
• Experience building and deploying LLM-based systems in production.
• Experience working in production environments with model monitoring and iteration.
• Experience with modern data science and ML ecosystems using Python.
• Experience working with large datasets and strong SQL skills.
• Understanding of LLM evaluation, prompt design, and system behavior.
• Strong foundation in statistics and machine learning fundamentals.
• Demonstrated ability to deliver production-grade AI systems end-to-end.
• Demonstrated ability to translate business needs into AI/ML solutions and communicate clearly.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

•  Experience with RAG architectures and retrieval systems.
• Experience designing or working with agent-based workflows.
• Experience with MLOps tools and production ML systems.
• Experience working in cloud environments (preferably Azure).