Sr. Principal Data Scientist (Agentic AI)

This senior principal-level individual-contributor role operates at the highest technical level at Warner Bros. Discovery, serving as a company-wide authority in advanced Data Science, Machine Learning, and Applied AI. The role designs and builds enterprise-grade agentic AI systems, including autonomous and multi-agent workflows that use reasoning, tool use, planning, memory, and orchestration to execute complex business processes.

• Act as one of the most senior technical individual contributors in Data Science and Machine Learning, setting technical direction and standards for complex ML implementations without direct people management.
• Lead end-to-end design and implementation of advanced ML systems across content intelligence and metadata enrichment, audience modelling and personalisation, forecasting, optimisation and experimentation, and advertising intelligence and monetisation analytics.
• Design and implement state-of-the-art models, including large-scale recommender systems, time-series forecasting and probabilistic models, causal inference, experimentation and uplift modelling, NLP, generative AI and multimodal ML systems, and computer vision and video intelligence pipelines.
• Apply rigorous statistical thinking, experimentation discipline, and scientific validation to all solutions, and serve as final technical reviewer for high-risk or high-impact ML solutions.
• Architect production-grade ML systems integrated with the cloud data ecosystem (AWS, Snowflake, GCP), and define best practices for feature engineering and feature stores, model lifecycle management and MLOps, CI/CD for ML, model monitoring, drift detection, reproducibility, governance And responsible AI.
• Partner deeply with data engineering, platform, and product engineering teams to ensure scalable, resilient delivery.
• Own and deliver mission-critical AI solutions across content performance prediction and ratings intelligence, marketing attribution and lifecycle analytics, search, discovery and ranking systems, ad load optimisation and pricing intelligence, and operational forecasting and automation.
• Translate complex modelling outputs into clear, executive-ready insights that drive decisions.
• Serve as a trusted technical advisor to senior leaders across Streaming, Content, Ad Sales, Marketing, and Technology, communicating complex ML concepts with clarity and credibility to non-technical stakeholders and influencing enterprise AI roadmaps, architectural decisions And investment priorities through expertise rather than hierarchy.
• Mentor senior and staff-level data scientists through technical guidance, design reviews, and deep problem-solving, contribute to internal AI communities of practice, technical forums, and standards bodies, and elevate overall engineering and scientific rigour across the Data Science organisation.

• Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, Operations Research, or related disciplines.
• 15–18+ years of experience, including 10–14 years of deep, hands-on expertise in Data Science, ML, and AI systems at enterprise scale.
• 18–20 years of total experience, with 13–15 years in Data Science/ML, including hands-on technical leadership.
• Deep expertise in predictive modelling, optimisation, and advanced ML techniques.
• Deep expertise in MLOps and large-scale model deployment.
• Deep expertise in modern cloud ecosystems (AWS/GCP/Snowflake).
• Deep expertise in Python, PyTorch, TensorFlow, SQL, and ML frameworks.
• Deep expertise in experiment design, causal inference, and statistical modelling.
• Demonstrated experience in Media & Entertainment, streaming, digital advertising, or consumer intelligence.
• Strong track record of delivering enterprise impact through AI solutions.
• Exceptional communication skills, including the ability to influence executives and inspire technical teams.

• Experience developing or customising Large Language Models or multimodal foundation models.
• Patent, publication, or conference-track record in ML/AI.
• Experience with video intelligence, computer vision for media workflows, or content metadata systems.
• Experience partnering with product and engineering organisations in a fast-paced environment.