Your New Role:  

The Sr. Principal, AdTech Data Scientist reports to the VP, Data Science & AI for AdTech and leads the design, development, and deployment of advanced data science models that power WBD’s global advertising ecosystem. This role owns the strategy and execution of ML/AI frameworks for forecasting, optimization, personalization, and audience intelligence. By combining deep technical expertise with strategic influence, the Sr. Principal transforms data into predictive insights that maximize monetization, enhance targeting precision, and enable automation across converged linear and digital platforms. 

Acting as both hands-on scientist and thought leader, the Sr. Principal partners with engineering, product, and sales to embed machine learning into the core of WBD’s advertising workflows. 

Advanced Modeling & AI Strategy  

• Define the vision and roadmap for machine learning, optimization, and AI systems that drive forecasting accuracy, yield optimization, and audience targeting. 

• Develop novel models in time-series forecasting, reinforcement learning, optimization, and causal inference tailored for advertising use cases. 

Experimentation & Innovation – 

• Design and oversee experimentation frameworks, A/B testing, and measurement systems to evaluate model impact. 

• Advance audience intelligence, personalization, and cross-platform reach/frequency models. 

• Explore emerging AI/ML approaches to maintain WBD’s competitive edge in advertising innovation. 

Leadership & Strategic Partnership  

• Act as a hands-on technical expert and advisor, translating data science into actionable strategies for sales, product, and operations stakeholders. 

• Mentor data scientists and engineers, building best practices across global teams. 

• Engage externally with AI/ML communities, vendors, and partners to influence industry direction and accelerate adoption of next-generation methods. 

Qualifications & Experience 

  Education: PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or related technical discipline required. Postdoctoral research or advanced specialization in optimization, machine learning, or large-scale AI systems strongly preferred. 

  Data Science Leadership: 15+ years of applied data science experience, with proven success in deploying ML models into production at enterprise scale (including MIPS-scale or equivalent high-throughput systems). 

  Advanced Modeling Expertise: Deep knowledge of statistical optimization, stochastic modeling, reinforcement learning, deep learning, and causal inference applied to advertising, media, or high-scale transactional domains. 

  Scalable ML Systems: Demonstrated experience building cloud-native ML/AI pipelines (AWS SageMaker, Bedrock, Databricks, TensorFlow, PyTorch, Spark ML) with focus on performance, cost efficiency, and scalability. 

  Optimization & Yield: Expertise in statistical optimization and decision science techniques for forecasting, yield management, and pricing algorithms in ad-tech or related industries. 

  Experimentation & Measurement: Strong background in A/B testing, multi-armed bandits, attribution modeling, and quantifying model-driven business impact. 

  Operational Excellence: Skilled in MLOps, CI/CD for ML, model governance, bias detection, and observability frameworks. 

  Communication & Influence: Proven ability to articulate advanced data science concepts to C-level executives and influence product, sales, and engineering stakeholders. 

  Industry Engagement: Active participation in ML/AI communities, publications, patents, or open-source contributions highly valued