Principal, Data Scientist

Warner Bros Discovery Warner Bros Discovery · Media · Hyderabad, Telangāna, India · Technology

Principal Data Scientist role focused on designing, developing, and deploying advanced data science models for Warner Bros. Discovery's global advertising ecosystem. The role involves ML/AI strategy for forecasting, optimization, personalization, and audience intelligence, with a hands-on approach to embedding machine learning into advertising workflows. Key responsibilities include developing novel models, designing experimentation frameworks, advancing audience intelligence, and optimizing data platforms. Requires 12+ years of experience in applied data science, expertise in various modeling techniques, scalable ML systems, optimization, experimentation, and MLOps.

What you'd actually do

  1. Define the vision and roadmap for machine learning, optimization, and AI systems that drive forecasting accuracy, yield optimization, and audience targeting.
  2. Develop novel models in time-series forecasting, reinforcement learning, optimization, and causal inference tailored for advertising use cases.
  3. Design and oversee experimentation frameworks, A/B testing, and measurement systems to evaluate model impact.
  4. Advance audience intelligence, personalization, and cross-platform reach/frequency models.
  5. Explore emerging AI/ML approaches to maintain WBD’s competitive edge in advertising innovation.

Skills

Required

  • 12+ years of applied data science experience
  • Deep knowledge of statistical optimization, stochastic modeling, reinforcement learning, deep learning, and causal inference
  • Demonstrated experience building cloud-native ML/AI pipelines (AWS SageMaker, Bedrock, Databricks, TensorFlow, PyTorch, Spark ML)
  • Expertise in statistical optimization and decision science techniques for forecasting, yield management, and pricing algorithms
  • Strong background in A/B testing, multi-armed bandits, attribution modeling, and quantifying model-driven business impact
  • Skilled in MLOps, CI/CD for ML, model governance, bias detection, and observability frameworks
  • Proven ability to articulate advanced data science concepts to C-level executives and influence product, sales, and engineering stakeholders

Nice to have

  • Active participation in ML/AI communities, publications, patents, or open-source contributions highly valued

What the JD emphasized

  • deploying ML models into production at enterprise scale
  • Advanced degree in Computer Science, Statistics, Applied Mathematics, Operations Research, or related technical discipline required.
  • Advanced specialization in optimization, machine learning, or large-scale AI systems strongly preferred.

Other signals

  • Develop novel models in time-series forecasting, reinforcement learning, optimization, and causal inference tailored for advertising use cases.
  • Advance audience intelligence, personalization, and cross-platform reach/frequency models.
  • Explore emerging AI/ML approaches to maintain WBD’s competitive edge in advertising innovation.
  • Deploying ML models into production at enterprise scale
  • Building cloud-native ML/AI pipelines