Data Scientist

What We’re Looking For

We are looking for someone who combines:

• strong engineering mindset,
• hands-on AI/LLM experience,
• and the ability to build scalable, production-ready solutions.

This is not a purely research-oriented Data Scientist role — we are looking for someone comfortable working close to production systems and modern cloud-based data platforms.

Required Skills

• Strong hands-on experience with:
  • Python,
  • PySpark,
  • SQL
• Practical experience with Generative AI:
  • LLMs,
  • prompting techniques,
  • RAG / GraphRAG,
  • Agentic AI concepts
• Experience with Azure ecosystem:
  • ADF,
  • Databricks,
  • SQL Server,
  • ADLS
• Experience in data analysis, transformation, and modelling
• Experience working with shared repositories and collaborative development:
  • Git / GitHub
• Understanding of scalable and maintainable data solution design

Nice to Have

• Experience with Neo4j, Cypher, knowledge graphs, or graph databases
• Experience working in Agile/Scrum environments
• Familiarity with Azure DevOps

We are looking for a Data Scientist with strong engineering capabilities and hands-on experience in Generative AI solutions. The role combines work on modern AI functionalities (LLM, RAG, Agentic AI) with data engineering and production-grade development within the Azure ecosystem.

You will work closely with cross-functional teams to build scalable, high-quality AI and data solutions used in real business environments.

Additional Information

• International environment
• Long-term cooperation

,[Develop and enhance functionalities related to Data Science and Generative AI, including: chatbots, Agentic AI solutions, RAG / GraphRAG implementations, Improve and optimize existing PySpark/Python code to ensure performance, maintainability, and alignment with coding standards, Develop and maintain data pipelines using Azure technologies: Azure Data Factory (ADF), Azure Databricks, SQL, Azure Data Lake Storage (ADLS), Perform robust data analysis, transformation, and interpretation, Collaborate closely with Consumption/API teams to integrate developed solutions and ensure compliance with engineering standards, Promote coding best practices and contribute to technical improvements across the team, Proactively identify opportunities to optimize Data Science solutions and services] Requirements: Python, PySpark, SQL, GenAI, LLM, Prompting Techniques, RAG, GraphRAG, Agentic AI Concept, Azure ecosystem, ADF, Databricks, SQL Server, ADLS, Data analysis, Data transformation, Data modeling, Git, GitHub, Neo4j, Cypher, Graph databases, Agile/Scrum, Azure DevOps