As a Senior Principal Data Scientist at NielsenIQ, you will be part of the Strategic Analytics and Insights team responsible for building and scaling globally deployed analytics and AI products that drive decision-making for retailers and manufacturers worldwide. Leveraging industry-leading data assets and modern cloud platforms, you will design always-on, production-grade AI systems embedded directly into client-facing and internal products. **Key Responsibilities:**
Lead the development of advanced AI and Generative AI solutions, focusing on Generative AI and Agentic AI systems such as LLM-based reasoning, planning, tool use, and orchestration. - Design and implement LLM-powered applications, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation frameworks. - Create agentic workflows that combine models, tools, memory, and business logic to solve complex, multi-step analytical and decision-making problems. - Translate ambiguous business and product challenges into scalable AI system designs, selecting the right modeling and GenAI approaches. - Rapidly prototype and validate new AI capabilities, then collaborate with Engineering to deliver secure, reliable, production-grade systems. - Define and maintain standards for model quality, performance, monitoring, and lifecycle management across ML and GenAI solutions. - Ensure AI systems meet enterprise expectations for governance, explainability, robustness, and responsible AI use. - Act as a technical leader and trusted advisor across Data Science, Product, Engineering, and Platform teams. - Effectively communicate complex technical concepts, trade-offs, and recommendations to both technical and non-technical stakeholders. - Drive initiatives end-to-end, aligning across multiple teams and managing dependencies in a fast-moving environment. - Mentor and guide other data scientists, promoting best practices in ML, GenAI system design, and software engineering. - Stay updated with advances in LLMs, multimodal models, agent frameworks, optimization techniques, and cloud-native AI architectures, translating them into practical, high-impact solutions. **Qualifications:**
Masters or PhD in Data Science, Computer Science, Machine Learning, Statistics, Mathematics, or related field. - 10+ years of experience building and deploying ML and AI systems in production environments. - Recent, hands-on experience with Generative AI and LLM-based applications. - Strong foundation in classical machine learning and statistical modeling. - Proficiency in Python, SQL, and PySpark in cloud analytics environments. - Experience deploying AI systems on cloud platforms and familiarity with Git-based workflows, CI/CD pipelines, and Agile development. - Excellent problem-solving and communication skills, with the ability to operate independently at a Principal level and influence senior stakeholders. **Additional Information:**
Our Benefits include a flexible working environment, volunteer time off, LinkedIn Learning, and Employee-Assistance-Program (EAP). As a leading consumer intelligence company, NielsenIQ is dedicated to delivering a comprehensive understanding of consumer buying behavior and fostering growth opportunities. With a commitment to diversity, equity, and inclusion, we invite individuals who share our values to join us in making a meaningful impact. As a Senior Principal Data Scientist at NielsenIQ, you will be part of the Strategic Analytics and Insights team responsible for building and scaling globally deployed analytics and AI products that drive decision-making for retailers and manufacturers worldwide. Leveraging industry-leading data assets and modern cloud platforms, you will design always-on, production-grade AI systems embedded directly into client-facing and internal products. **Key Responsibilities:**
Lead the development of advanced AI and Generative AI solutions, focusing on Generative AI and Agentic AI systems such as LLM-based reasoning, planning, tool use, and orchestration. - Design and implement LLM-powered applications, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation frameworks. - Create agentic workflows that combine models, tools, memory, and business logic to solve complex, multi-step analytical and decision-making problems. - Translate ambiguous business and product challenges into scalable AI system designs, selecting the right modeling and GenAI approaches. - Rapidly prototype and validate new AI capabilities, then collaborate with Engineering to deliver secure, reliable, production-grade systems. - Define and maintain standards for model quality, performance, monitoring, and lifecycle management across ML and GenAI solutions. - Ensure AI systems meet enterprise expectations for governance, explainability, robustness, and responsible AI use. - Act as a technical leader and trusted advisor across Data Science, Product, Engineering, and Pla
