Data Scientist with AI

At Devapo, we focus on continuous self-development and acquiring new knowledge. We provide our clients with tools that allow their businesses to flourish, ensuring long-term goals are met.

• Minimum 4+ years of experience in Data Science or similar role, with at least 1+ year hands-on experience in Generative AI/LLMs.
• Strong programming proficiency in Python including libraries like PyTorch, TensorFlow, or scikit-learn.
• Hands-on experience with major cloud AI platforms: Azure OpenAI, GCP Vertex AI, or AWS Bedrock/SageMaker.
• Deep understanding of LLMs, embeddings, vector databases, and RAG architectures.
• Proficiency in SQL and experience with large, complex datasets in cloud environments.
• Solid foundation in statistics, probability, and experimental design (A/B testing).
• Familiarity with containerization (Docker) and orchestration (Kubernetes/MLOps tools) for deploying models at scale.
• Excellent communication skills in English (minimum B2 level) and ability to collaborate with technical and business stakeholders.

Nice to have:

• Experience with multi-agent systems, behavior trees, or reinforcement learning.
• Background in regulated industries (finance, insurance, healthcare).
• Experience with Databricks or Apache Spark ecosystem.

• Lead end-to-end projects in Data Science, Machine Learning, Generative AI, and Large Language Models (LLMs) from research to production deployment.
• Design and implement scalable AI/ML pipelines and MLOps practices using cloud-native services (Azure Machine Learning, GCP Vertex AI, AWS SageMaker).
• Develop, optimize, and evaluate LLM-based applications including Retrieval-Augmented Generation (RAG) systems using vector stores and prompt orchestration.
• Collaborate with Data Engineers and BI teams to ensure access to high-quality, well-structured data for model training and inference.
• Apply advanced statistical analysis, experimentation (A/B testing, causal inference), and modeling techniques to solve complex business problems.
• Contribute to defining AI roadmaps aligned with business objectives and driving measurable impact.
• Ensure adherence to AI governance, security, and data compliance standards within regulated environments.
• Research and evaluate new AI frameworks (LangChain, CrewAI) and technologies (multi-modal AI, agentic workflows).