Principal Data Scientist

Description

Storytelling is central to the company's work, which spans studios, direct-to-consumer services and TV media, with a broad portfolio of brands.

The company's teams move quickly, think boldly and work together toward results.

This principal data scientist role covers machine learning and data science work across the company's global businesses and suits a senior technical leader.

You will turn business problems into scalable analytics, lead end-to-end ML model development and keep models reliable in production.

You will work with product, engineering, technology and business partners.

Media and entertainment experience, including content, streaming, audience behavior, ad intelligence or metadata systems, is a significant plus.

Responsibilities

• Design, build and scale advanced ML models for predictive analytics, NLP, computer vision, forecasting, optimization and recommender systems.
• Apply hypothesis testing, probability modeling, causal inference and experiment design to complex business questions.
• Build models that can be interpreted and explained, while keeping them reproducible and robust in operation.
• Handle feature engineering, model selection, hyperparameter tuning and validation with current ML frameworks.
• Turn vague problems into structured analyses with measurable impact.
• Build production ML pipelines that connect to the company's data platforms, including Snowflake, AWS, GCP and Databricks.
• Set up CI/CD, model monitoring, drift detection, alerting and performance governance.
• Help design feature stores, experimentation platforms and ML observability frameworks.
• Work with data engineering and platform teams so models deploy reliably at scale.
• Lead ML delivery in content performance and ratings prediction, audience segmentation, churn and lifetime value modeling, search ranking and personalization, metadata enrichment with NLP and CV, and operational forecasting and automation.
• Turn analytical results into practical, high-return recommendations for product and business stakeholders.
• Work with senior leaders in streaming, technology, product, content and marketing.
• Explain complex modeling results clearly to non-technical audiences so they can shape decisions.
• Shape analytical roadmaps that match enterprise priorities.
• Mentor data scientists and ML engineers to raise scientific rigor and practice standards.
• Lead project teams through experimentation, modeling, evaluation and productionization.
• Encourage knowledge sharing, documentation standards and internal communities of practice.
• Champion responsible AI, model governance and ethical data use.

Requirements

• A master's degree is required, and a Ph.D. is preferred, in computer science, data science, machine learning, statistics, mathematics or a related field.
• 14, 16 years of total experience, including 10, 12 years in data science, ML and advanced analytics.
• Hands-on depth in predictive modeling, optimization, deep learning, NLP and computer vision.
• Working skill in Python, SQL, PyTorch or TensorFlow, Scikit-learn and other ML frameworks.
• Experience with MLOps, model deployment, monitoring and observability.
• Statistical modeling, experiment design and Bayesian methods.
• Experience with cloud platforms such as AWS, GCP or Snowflake.
• A proven record of business impact from ML solutions in large-scale environments.
• Strong communication skills and the ability to influence cross-functional teams.
• Preferred: experience in media and entertainment, streaming, digital advertising, metadata or audience intelligence.
• Preferred: hands-on exposure to foundation models, LLMs, embeddings or generative AI.
• Preferred: experience with video intelligence, OCR and CV pipelines, or content metadata engines.
• Preferred: publications, patents or conference-level contributions in ML or AI.

Conditions

Qualified candidates who need accommodations during recruitment can request them through the company's accessibility page.