Machine Learning Scientist IV, Content & Conversation Modeling

What you'll do

• Develop and optimize predictive models to inform content strategy, valuation, and scheduling.
• Manage the end-to-end machine learning lifecycle from feature engineering to deployment and monitoring.
• Translate ambiguous business problems into practical technical solutions using machine learning.
• Partner with analytics teams to implement models for global performance tracking.
• Influence data and ML infrastructure development in collaboration with engineering and MLOps teams.
• Communicate complex technical concepts clearly to cross-functional partners with varying technical backgrounds.
• Build modular, scalable code designed for team resilience and production deployment.

What we're looking for

• An advanced degree (MS or PhD) in Computer Science, Economics, Physics, Statistics, Mathematics, or a related technical field.
• Focus on machine learning and predictive modeling during academic studies.
• Relevant experience in one or more machine learning roles.
• Strong experience in Python and an ML/DL framework such as scikit-learn, Keras, PyTorch, TensorFlow, MetaFlow, or JAX.
• Proven track record of delivering business solutions leveraging Machine Learning.
• Ability to translate ambiguous problem spaces into practical technical solutions.
• Exceptional communication skills to explain complex technical concepts to cross-functional partners.
• Deep familiarity with the ML lifecycle and strong technical judgment for deploying models in production.