Senior Member Technical Staff ( Lead AI Data Science Engineer)

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

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.

 

Role Overview:

As a Lead Data Science Engineer on the Gracenote Media team, you will be responsible for

defining the AI/ML strategy, overseeing large-scale data science projects, and leading teams to

build cutting-edge machine learning solutions that scale content understanding and generation,

entity linkage, and more to achieve the scale that matches our customer’s demands.

Key Responsibilities:

● Define and execute the AI/ML strategy for content generation (Gen-AI), entity linkage

and matching, image processing, and content understanding.

● Lead the development of next-generation content generation systems using Large

Language Models (LLMs)

● Architect scalable data platforms to support real-time and batch processing of media-rich

datasets.

● Own the Data Quality of the deliverables and ensure the consistent performance of the

models and its output quality.

● Define and implement standards for the organization that match industry best practices.

● Collaborate with product, engineering, and business teams to drive AI-powered

innovation.

● Improve computer vision models for automated content tagging, video summarization,

and understanding.

● Oversee MLOps infrastructure to ensure robust deployment and monitoring of ML

models.

● Stay ahead of emerging trends in AI, deep learning, and media tech, integrating new

research into practical applications.

● Mentor and grow a team of data scientists and engineers.

Required Skills:

● Expert-level proficiency in Python, SQL, and big data tools (Spark, Kafka, Airflow).

● Extensive experience in deep learning, reinforcement learning, NLP, and computer

vision.

● Experience in large-scale machine learning model deployment and optimization.

● Proven leadership skills in building and scaling data science teams.

● Experience with Kubernetes, Docker, and cloud AI services.

Master’s in AI, Machine Learning, Data Science, or a related field.

● 8+ years of experience in data science and machine learning, with at least 3+ years

leading teams.

● Strong track record in building AI-driven solutions for media and entertainment.

Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.