Job Description

Company Description

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.

Role Overview:

A Lead Data Science Engineer in a Media Tech company is responsible for defining the AI/ML strategy, overseeing large-scale data science projects, and leading teams to build cutting-edge machine learning solutions that drive content personalization, user retention, and monetization.

Key Responsibilities:

Define and execute the AI/ML strategy for content discovery, ad-tech, and audience analytics. Lead the development of next-generation recommendation systems using deep learning, reinforcement learning, and graph-based models. 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, implement Standards, nomenclatures best practices and ensure detailed documentation is captured for all deliverables. Collaborate with product, engineering, and business teams to drive AI-powered innovation. Improve computer vision models for automated content tagging, video summarization, and speech-to-text transcription. Enhance monetization strategies by optimizing ad targeting models and revenue prediction algorithms. 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.

Qualifications

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. Strong expertise in personalization algorithms, graph-based models, and real-time recommendation engines. Experience in large-scale machine learning model deployment and optimization. Deep understanding of ad-tech models, real-time bidding, and programmatic advertising. Proven leadership skills in building and scaling data science teams. Experience with Kubernetes, Docker, and cloud AI services.

Qualifications:

Master's in AI, Machine Learning, Data Science, or a related field. 7+ 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.

Additional Information

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