Senior Principal Data Scientist The NielsenIQ Strategic Analytics and Insights team builds and scales globally deployed analytics and AI products that power decision‑making for retailers and manufacturers worldwide. Leveraging industry‑leading data assets and modern cloud platforms, we design always‑on, production‑grade AI systems embedded directly into client‑facing and internal products. We are hiring a Principal Data Scientist with deep expertise in Machine Learning, Generative AI, and Agentic AI systems. This is a senior, hands‑on technical role for an experienced AI practitioner who has designed, built, and deployed LLM‑powered systems in production, not just experimented with them. In this role, you will work closely with Product, Engineering, and Platform teams to take ideas from concept through deployment, while influencing AI architecture, standards, and best practices across the organization. Lead Advanced AI & Generative AI Solutions Design, develop, and deploy advanced AI/ML systems, with a strong focus on Generative AI and Agentic AI (e.g., LLM‑based reasoning, planning, tool use, and orchestration). Architect and implement LLM‑powered applications, including prompt engineering, retrieval‑augmented generation (RAG), fine‑tuning, and evaluation frameworks. Design 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. Build From Prototype to Production Rapidly prototype and validate new AI capabilities, then partner with Engineering to deliver secure, reliable, production‑grade systems. Define and uphold 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. Influence and Collaborate Across Teams Act as a technical leader and trusted advisor across Data Science, Product, Engineering, and Platform teams. Clearly 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 Shape Technical Excellence Mentor and guide other data scientists, promoting best practices in ML, GenAI system design, and software engineering. Stay current with advances in LLMs, multimodal models, agent frameworks, optimization techniques, and cloud‑native AI architectures, and help translate them into practical, high‑impact solutions.
Experience & Expertise Master’s or PhD in Data Science, Computer Science, Machine Learning, Statistics, Mathematics, or a 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, including: Prompt engineering and systematic evaluation Retrieval‑augmented generation (RAG) Model fine‑tuning or adaptation techniques Agentic or multi‑agent system architectures Strong foundation in classical machine learning and statistical modeling, with good judgment about when GenAI is (and is not) the right solution. Experience with optimization techniques (e.g., linear or integer programming, constrained optimization) is a plus. Engineering & Platform Skills Advanced proficiency in Python, with experience using SQL and PySpark in cloud analytics environments. Hands‑on experience deploying AI systems on cloud platforms (e.g., Azure, GCP, or equivalent), including MLOps and LLMOps practices. Familiarity with Git‑based workflows, CI/CD pipelines, and Agile development. Business Context & Communication Experience working with large‑scale transactional or behavioral datasets (retail, CPG, FMCG, or similar domains is a plus). Excellent problem‑solving and communication skills, with the ability to operate independently at a Principal level and influence senior stakeholders. Why Join NielsenIQ Build real, production AI systems used by global clients—not just experiments or demos. Shape how Generative and Agentic AI are applied responsibly at enterprise scale. Influence long‑term AI architecture and standards across a global analytics organization. Work on complex, high‑impact business problems with talented peers across data science, engineering, and product.
Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluat