Data Scientist

Design, implement, and administer AI solutions on Azure AI Foundry for enterprise-scale workloads. Build and fine-tune Generative AI models leveraging Azure OpenAI, BERT, ROUGE, Mistral, Claude/Sonnet/Anthropic. Develop AI workflows using Copilot Studio Agents, Agent-to-Agent communication, and MCP (Model Control Protocol). Implement and optimize AI Core algorithms such as XGBoost, Bayesian networks, and Random Forest for predictive analytics and forecasting. Ensure end-to-end model lifecycle management including training, deployment, monitoring, and retraining. Integrate Generative AI capabilities into enterprise applications using secure and scalable architectures. Collaborate with data scientists, engineers, and business teams to convert business needs into AI solutions. Utilize MLOps pipelines for CI/CD, model versioning, and automated deployments in Azure. Monitor performance, capacity, and cost metrics for AI infrastructure and optimize as needed. Enforce AI governance, security, compliance, and responsible AI principles across all solutions. Required Skill Set 5+ years of hands-on experience in AI/ML development and administration within Azure ecosystem. Strong expertise in Azure AI Foundry, BERT, ROUGE, and Generative AI frameworks. Proficiency with AI Core algorithms such as XGBoost, Bayesian models, and Random Forest. Experience working with Azure OpenAI, Copilot Studio Agent, Agent-to-Agent orchestration, and MCP. Strong programming skills in Python and experience with frameworks like PyTorch, TensorFlow. Knowledge of model evaluation techniques, bias detection, and ethical AI principles. Hands-on experience in MLOps, CI/CD for AI, and infrastructure automation in Azure. Understanding of vector databases, embeddings, and RAG (Retrieval-Augmented Generation) workflows.