Data Science Lead - R01572475

Job requirements

Experience Range: With at least 7 to 10 years of experience in AI, advanced analytics, cloud platforms, and solution architecture, including demonstrated expertise in translating business requirements into scalable, secure, production-ready AI solutions Key Responsibilities:
• Architect and deliver enterprise AI platforms and advanced analytics solutions that align with business objectives and drive measurable outcomes
• Translate complex business use cases into scalable AI, analytics, and technology architectures leveraging modern cloud and AI capabilities
• Design and implement AI solutions utilizing Azure Foundry, Azure AI services, and cloud-native technologies to ensure scalability, security, and production readiness
• Define architecture patterns and frameworks for Generative AI, machine learning, advanced analytics, and intelligent applications
• Collaborate with business, data, engineering, and platform teams to drive AI initiatives from ideation through implementation
• Establish standards and best practices for AI platform engineering, integration, governance, security, and operationalization
• Evaluate emerging AI platform capabilities and technologies to identify opportunities for improving business outcomes
• Provide architectural guidance to delivery teams and stakeholders to ensure AI investments are aligned with enterprise priorities
Required Skills:
• Microsoft Azure AI technologies, including Azure Foundry and Azure AI services
• Designing scalable, secure, and production-ready AI and analytics solutions
• Generative AI, machine learning, and advanced analytics architectures
• Enterprise cloud platforms and data platform engineering
• API design, integration patterns, and modern AI solution architectures
• AI governance, security, responsible AI, and operationalization best practices
• MLOps and AI platform automation
Preferred Skills:
• Leading enterprise AI transformation and platform modernization initiatives
• GenAI patterns, including LLM applications, Retrieval-Augmented Generation (RAG), agents, prompt engineering, and AI orchestration
• Building reusable AI platforms and accelerators for enterprise-scale adoption
• LLMOps, AI observability, and model lifecycle management
• Connecting AI platform capabilities to measurable business outcomes
Desired Qualifications:
• Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline
• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Azure AI Engineer Associate