Senior Data Science Engineer

Gracenote, a Nielsen company, is dedicated to connecting audiences to the entertainment they love, powering a better media future for all people. Gracenote is the content data business unit of Nielsen that powers innovative entertainment experiences for the world’s leading media companies. Our entertainment metadata and connected IDs deliver advanced content navigation and discovery to connect consumers to the content they love and discover new ones.Gracenote’s industry-leading datasets cover TV programs, movies, sports, music and podcasts in 80 countries and 35 languages. Gracenote provides common identifiers that are universally adopted by the world’s leading media companies enabling powerful cross-media entertainment experiences. Machine driven, human validated best-in-class data and images fuel new search and discovery experiences across every screen.Gracenote's Data Organization is a dynamic and innovative group that is essential in delivering business outcomes through data, insights, predictive & prescriptive analytics. An extremely motivated team that values creativity, experimentation through continuous learning in an agile and collaborative manner. The data team oversees the whole data lifecycle – from designing, developing and maintaining data architecture that satisfies our business goals to managing data governance and region-specific regulations. 
Role Overview:
As a Senior Data Science Engineer on the Gracenote Media team, you will lead the application of advanced machine learning models and big data solutions that power content understanding and generation, entity linkage, and more in order to achieve the scale that matches our customer’s demands.

Key Responsibilities:

• Lead the design, development and deployment of scalable machine learning models in order to solve problems in natural language processing and/or computer vision problems within content generation and enhancement, machine translation, automated tagging, and content understanding.
• Develop and maintain large scale data architectures that support our data science capability including data pipelines that process vast amounts of video, audio, and textual metadata, centralized feature stores and ML ops pipelines. 
• Work with computer vision models for video analysis, captioning, and scene recognition.
• Automate MLOps workflows for seamless deployment and monitoring of AI models.
• Implement Data Quality frameworks to ensure the model outputs and data pipelines are of highest quality.
• Mentor junior data scientists and help to develop their skills and expertise.
• Stay current with the latest in the industry and bring best practice to the organization in data science & ML engineering space.

Required Skills:

• Strong expertise in Python, SQL, and big data tools (Spark, Kafka, Flink).
• Hands-on experience with deep learning and NLP (BERT, GPT, Transformer models).
• Experience in computer vision models for media processing and content moderation.
• Experience developing & deploying both online and offline models.
• Experience in distributed computing and cloud platforms (AWS, GCP, Azure).

Qualifications:

• Bachelor’s/Master’s degree in Data Science, Machine Learning, or related fields.
• 5+ years of experience in data science, machine learning, or data engineering.
• Proven experience working with media datasets and AI-driven content platforms.