Description

Key Skills: Machine Learning, Python, SQL, PyTorch, TensorFlow, Scikit-learn, MLOps, Statistical Modeling, AWS, GCP

Good to Have Skills: Experience in Media & Entertainment, streaming, digital advertising, metadata, or audience intelligence. Hands-on exposure to foundation models, LLMs, embeddings, or generative AI. Experience with video intelligence, OCR/CV pipelines, or content metadata engines. Publications, patents, or conference-level contributions in ML/AI. Deep learning, NLP, Computer Vision, Snowflake, Databricks, Bayesian methods, experiment design.

Roles & Responsibilities:

• Design, build, and scale advanced machine learning models across predictive analytics, NLP, CV, forecasting, optimization, and recommender systems.
• Apply strong statistical foundations including hypothesis testing, probability modeling, causal inference, and experiment design to solve complex business problems.
• Develop interpretable and explainable ML models, ensuring scientific rigor, reproducibility, and operational robustness.
• Build production-grade ML pipelines integrating with WBD's data ecosystem including Snowflake, AWS, GCP, and Databricks.
• Implement CI/CD, model monitoring, drift detection, alerting, and model performance governance systems.
• Lead delivery of ML solutions for content performance prediction, audience segmentation, churn modeling, and personalization systems.
• Partner with senior leaders across Streaming, Technology, Product, Content, and Marketing departments.
• Present complex modeling results clearly to non-technical audiences, influencing business decisions with data-driven insights.
• Mentor data scientists and ML engineers, elevating scientific rigor and best practices across the team.
• Champion responsible AI, model governance, and ethical data usage across all engagements.

Experience Required: 14–16 years of total experience, with 10–12 years in Data Science, ML, and advanced analytics. Demonstrated track record of delivering business impact through ML solutions in large-scale environments.

Education: Master's degree (or Ph.D. preferred) in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related fields

Key Skills

Education

Any Graduate