Principal Data Scientist

Responsibilities

• Shape the technical vision for AI/ML across the content product ecosystem, identifying high-impact opportunities for Generative AI and computer vision.
• Architect complex, multimodal machine learning systems that integrate visual, audio, and textual data at petabyte scale.
• Design horizontal foundational capability layers to replace siloed builds with unified, scalable platforms.
• Oversee the development of high-performance inference systems using GPU acceleration and optimization techniques like quantization and pruning.
• Define rigorous evaluation frameworks leveraging A/B testing, offline/online evals, and human-in-the-loop reviews.
• Mentor the data science and ML engineering communities and partner with executive leadership to align engineering goals with strategic vision.

Requirements

• 10+ years of experience in machine learning.
• 2+ years of experience working with LLMs, diffusion models, or other generative image/video models.
• Expert-level proficiency in Python, Java, or C++.
• Deep learning framework expertise (PyTorch or TensorFlow).
• Extensive experience in computer vision, including object detection (YOLO) and image segmentation (Mask R-CNN).
• Proven track record with Big Data and MLOps tools (Spark, Flink, Kafka, Kubernetes, Airflow, or SageMaker).
• Ph.D. or Master’s degree in Computer Science, Machine Learning, Data Science, or a related quantitative field.

About the Company

Nielsen is dedicated to powering a better media future by providing powerful insights that drive client decisions. Through Gracenote, a Nielsen company, we connect audiences to the entertainment they love by providing industry-leading entertainment metadata and connected IDs for the world's leading media companies.