GenAI Insights Specialist at NielsenIQ

We are looking for a GenAI Insights Specialist to join our team and help translate the capabilities of large language models into measurable business value across consumer-facing industries such as FMCG, retail, and automotive. In this role, you will design, evaluate, and optimize generative AI solutions across the lifecycle — from problem framing and prompt engineering to evaluation frameworks, cost optimization, and insight delivery to marketing, brand, and commercial stakeholders. You will sit at the intersection of applied AI, marketing analytics, and product, partnering closely with data scientists, engineers, and business teams to turn unstructured consumer, campaign, and category data into trustworthy, production-grade GenAI insights. Key Responsibilities • Design, develop, and refine prompts and prompt chains for a range of GenAI use cases including summarization, classification, extraction, reasoning, and Q&A over enterprise data. • Build and maintain evaluation frameworks (offline and online) covering accuracy, faithfulness, hallucination rate, bias, latency, and cost, using both automated metrics and human-in-the-loop review. • Conduct systematic experimentation across models, prompting techniques (few-shot, CoT, ReAct, self-consistency, etc.), and retrieval strategies; document trade-offs and recommend the best configurations. • Drive token and cost optimization through prompt compression, context pruning, caching, batching, model routing, and selection of the right model tier for each task. • Partner with engineering on RAG pipelines, agentic workflows, and tool use; identify failure modes and propose mitigations. • Translate model outputs into clear insights, dashboards, and narratives for business stakeholders; quantify impact and ROI of GenAI initiatives. • Apply GenAI to marketing analytics use cases such as consumer review mining, social listening, campaign performance summarization, creative analysis, category and competitor intelligence, shopper insights, and brand health tracking. • Stay current with the rapidly evolving GenAI landscape (new models, techniques, benchmarks, safety practices) and bring relevant innovations into the team. • Contribute to responsible AI practices: red-teaming, prompt injection awareness, PII handling, and compliance considerations.