GenAI Insights Specialist

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.

• 3–5 years of experience in data science, machine learning, analytics, or applied AI, with at least 1–2 years working hands-on with LLMs / GenAI in a production or near-production setting.
• Strong conceptual understanding of generative AI fundamentals: transformer basics, tokenization, context windows, temperature/top-p, embeddings, fine-tuning vs. prompting vs. RAG, and where each fits.
• Demonstrated expertise in prompt engineering — including structured prompting, few-shot design, chain-of-thought, role/system prompting, output formatting (JSON/schema), and handling edge cases.
• Hands-on experience designing and running LLM evaluations — building golden datasets, defining rubrics, using LLM-as-a-judge responsibly, and interpreting results to drive iteration.
• Practical understanding of token economics and optimization — measuring input/output tokens, reducing context bloat, leveraging caching, choosing cost-appropriate models, and tracking spend per use case.
• Proficiency in Python and comfort with at least one major LLM SDK or framework (e.g., Anthropic, OpenAI, LangChain, LlamaIndex, DSPy).
• Strong analytical and communication skills — able to explain technical trade-offs to non-technical audiences and tell a clear story with data.
• Solid grounding in marketing analytics concepts — consumer segmentation, brand and campaign measurement, funnel and attribution basics, category/share of voice, and the typical KPIs used by marketing and commercial teams.
• Working exposure to one or more consumer-facing industries such as FMCG / CPG, retail, e-commerce, or automotive, with an understanding of the data landscape (POS, syndicated panel data like Nielsen/Kantar, CRM, social, reviews, dealership/aftersales data, etc.) and the questions stakeholders typically ask.
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field (or equivalent practical experience).

Nice to Have

• Experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector, etc.), and embedding model selection.
• Exposure to agentic frameworks, tool use, and multi-step workflows.
• Familiarity with observability tools for LLMs (LangSmith, Langfuse, Arize, Helicone, or similar).
• Experience with fine-tuning, LoRA/PEFT, or distillation for cost reduction.
• Background in NLP prior to the LLM era (classical methods, transformer fine-tuning).
• Prior experience in a consumer insights, market research, or marketing science function (agency, consulting, or in-house brand/retail/auto team).
• Familiarity with syndicated data providers (Nielsen, Kantar, Circana/IRI, GfK, JATO, etc.) and common marketing tech stacks.
• Experience operating in a regulated environment (finance, healthcare, etc.) with awareness of compliance and data privacy constraints.

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 evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies.

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

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Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence.  All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion