NEORIS - Senior Data Scientist

• 🔹 Machine Learning & AI Solutions• Build, train, evaluate, and optimize machine learning models for production and business applications.• Develop and support Generative AI solutions, including applications leveraging LLMs, embeddings, prompt engineering, and RAG-based architectures.• Support deployment and monitoring of ML and AI models in collaboration with engineering and MLOps teams. • 🔹 Data Engineering & Visualization• Work with structured and unstructured data sources to prepare datasets for analysis and modeling.• Develop dashboards, visualizations, and reports to communicate insights effectively to stakeholders.• Collaborate with data engineers to improve data pipelines and analytical workflows. • 🔹 Business Collaboration• Partner with business stakeholders to understand requirements and identify opportunities for data-driven improvements.• Translate technical findings into actionable insights and strategic recommendations.• Support decision-making through data storytelling and executive-level presentations. • 🔹 Innovation & Best Practices• Stay current with emerging trends in Data Science, AI, Machine Learning, and Generative AI.• Promote best practices in experimentation, reproducibility, documentation, and model governance.• Mentor junior team members and contribute to technical knowledge sharing. • Required Qualifications• 7+ years of experience in Data Science, Advanced Analytics, or Machine Learning roles.• Strong proficiency in Python and SQL for data analysis and model development.• Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost.• Practical experience designing or implementing Generative AI solutions, including: Large Language Models (LLMs), Prompt engineering, Embeddings and semantic search, Retrieval-Augmented Generation (RAG)• Strong background in: Statistical analysis, Predictive modeling, Feature engineering, Model evaluation and optimization.• Experience working with large datasets and cloud-based analytics environments.• Familiarity with ML deployment concepts and collaboration with engineering teams.• Experience with data visualization tools such as Tableau, Power BI, or similar.• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.• English – Advanced (required).