Senior Staff Engineer - Data Science

Warner Bros. Discovery•New York, NY

About The Position

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role: The Sr. Staff, AdTech Data Scientist is accountable for developing, deploying, and monitoring ML/AI systems that process billions of daily ad signals across linear and digital platforms. This role ensures predictive intelligence is integrated into advertising workflows to improve yield, optimize targeting, and accelerate campaign performance at global scale.

Requirements

Education: PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or related field strongly preferred; Master’s with equivalent applied experience considered.
Data Science Expertise: 12+ years of experience applying ML and advanced statistical methods to large-scale, production systems.
Optimization & Forecasting: Deep expertise in time-series forecasting, reinforcement learning, statistical optimization, and causal inference.
AdTech Domain Knowledge: Familiarity with advertising ecosystems including forecasting, yield optimization, identity resolution, and programmatic targeting.
Scalable ML Systems: Hands-on experience building ML pipelines in cloud-native environments using AWS SageMaker, Bedrock, Databricks, TensorFlow, PyTorch, Spark ML.
Experimentation & Measurement: Strong track record of designing and analyzing experiments to measure business impact of models at revenue scale.
Operational Excellence: Skilled in MLOps, model governance, explainability, and observability frameworks.
Collaboration & Influence: Ability to partner with engineers, product managers, and business stakeholders to deliver monetization-focused outcomes.

Responsibilities

Forecasting & Optimization Models – Build and deploy advanced forecasting, yield management, and pricing models leveraging statistical optimization, reinforcement learning, and decision science, driving efficiency across multi-billion-dollar annual ad spend.
Audience & Identity Intelligence – Develop algorithms for audience segmentation, cross-platform deduplication, and identity enrichment, ensuring privacy-compliant personalization and cross-device measurement across millions of users.
Production ML Systems – Operationalize ML pipelines with feature engineering, training, deployment, and monitoring, ensuring scalability and reliability on cloud-native platforms (AWS SageMaker, Bedrock, Databricks).
Collaboration & Mentorship – Partner with engineering and product teams to integrate models into business workflows; mentor junior data scientists in advanced ML methods and experimentation.