Description
Key Skills: Machine Learning, Python, Deep Learning, NLP, Computer Vision, PyTorch, TensorFlow, SQL, AWS, Statistical Modeling
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. Cloud platforms experience with GCP and Snowflake. Bayesian methods and experiment design expertise.
Roles & Responsibilities:
- Design, build, and scale advanced machine learning models across predictive analytics, NLP, computer vision, 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 across all implementations.
- Build production-grade ML pipelines integrating with WBD's data ecosystem including Snowflake, AWS, GCP, and Databricks platforms.
- Implement CI/CD, model monitoring, drift detection, alerting, and model performance governance for all deployed solutions.
- 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 to drive data-driven business decisions.
- Mentor data scientists and ML engineers, elevating scientific rigor and best practices across the entire team.
- Present complex modeling results clearly to non-technical audiences, influencing business decisions with actionable data-driven insights.
- Champion responsible AI, model governance, and ethical data usage across all analytical engagements and projects.
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