Data Scientist - AI at NielsenIQ

Job Responsibilities: As a Data Scientist on our team, you will: Design and deploy end-to-end machine learning solutions to solve diverse businesschallenges such as: • Using LLMs to allow users to interact with internal business systems • Understanding and classifying Product Images • Structuring and extracting insights from text data • Inferring product attributes • Detecting anomalies • Matching products across catalogsMaintain and optimize existing models to improve performance and maximize business impact Collaborate cross-functionally with product managers, data analysts, software engineers, DevOps, and solution architects to translate ideas into scalable solutions Integrate LLM and ML models into business processes, working closely with multidisciplinary development and business teams Continuously grow your technical expertise, staying up to date with the latest tools, frameworks, and best practices in data science Document model development workflows to ensure reproducibility and transparency Communicate complex technical concepts clearly and effectively to non-technical stakeholders throughout the development lifecycle Requirements We’re looking for someone who brings: Proficiency in Python and its data science ecosystem (e.g., NumPy, pandas, matplotlib,seaborn, scikit-learn, TensorFlow and/or Keras) At least 1-2 years of hands-on experience in data science roles, with a focus on: • Natural Language Processing (e.g., categorization, Named Entity Recognition) • Content Generation (e.g., Using LLMs to create marketing copy) • Computer Vision (e.g., image classification, object detection)Proficincy using LLM for multiple tasks, including Image classification, question answer and tool use Strong coding practices, including writing clean, well-documented, and maintainable code Experience with version control systems, such as Git Solid understanding of relational databases and SQL Excellent communication skills in English, both written and verbal Proven ability to collaborate and present to stakeholders with varying levels of technical expertise Nice to Have Experience with Azure ML Workspace or other cloud-based ML platforms Experience with LLM tools such as PromptFlow, Microsoft Agent Framework, LangChain, LangGraph Familiarity with spaCy and Hugging Face Transformers Experience working with architects, test engineers, platform engineers, and other data scientists in a collaborative environment