Senior Data Scientist - Data Platform Team, Hyderabad

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.

Senior Data Scientist (Data Platform Team), Hyderabad

About Warner Bros. Discovery

Warner Bros. Discovery is a premier global media and entertainment company, offering audiences the world's most differentiated and complete portfolio of content, brands, and franchises across television, film, streaming, and gaming. The new company combines Warner Media's premium entertainment, sports, and news assets with Discovery's leading non-fiction and international entertainment and sports businesses.

For more information, please visit www.wbd.com.

Meet our Team

The Data Platform team at Warner Bros. Discovery powers data-driven experiences across global products like Max, Discovery+, Sports, Studios, and News. The team builds and operates a scalable, multi-tenant data ecosystem that enables analytics, real-time insights, and machine learning use cases across the organization. Positioned at the core of the data journey, the team is responsible for ingesting, processing, and transforming large volumes of client and server-side data into reliable and high-quality datasets. Operating at the intersection of data and platform engineering, the team focuses on building robust pipelines, ensuring data quality and governance, and driving innovation in real-time processing, observability, and modern data infrastructure. The team collaborates closely with product, analytics, and engineering stakeholders to enable data-driven decision-making at scale.

• Design, develop, and deploy machine learning models and data science solutions at scale.
• Build ML capabilities using recommendation systems, personalization, predictive modeling, NLP, Generative AI, and Large Language Models (LLMs).
• Develop end-to-end ML workflows including data preparation, feature engineering, model training, validation, deployment, monitoring, and optimization.
• Apply advanced data science techniques including regression, classification, time series forecasting, causal inference, optimization techniques, and deep learning approaches.
• Build and improve scalable ML training and inference pipelines.
• Work closely with Data Engineers, ML Engineers, Product Managers, and business teams to deliver data-driven solutions.
• Perform experimentation, A/B testing, statistical analysis, and model evaluation to measure model effectiveness.
• Research and apply modern ML techniques including Transformers, Deep Learning models, NLP techniques, and AI-based solutions.
• Follow and promote data science best practices for model development, evaluation, and deployment.
• Mentor junior team members and provide technical guidance when required.
• Leverage AI-assisted tools to improve productivity and quality.

• Bachelor's/Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 5+ years of experience in building data science models and machine learning solutions.
• Strong understanding of statistics, machine learning algorithms, probability, and data science fundamentals.
• Hands-on experience in developing, deploying, and optimizing ML models in production environments.
• Strong programming experience with Python, R, Scala, or similar programming languages.
• Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, XGBoost, Keras, and Spark ML.
• Strong knowledge of machine learning techniques, including Regression & Classification Models, Time Series Forecasting, Recommendation Systems, Personalization, Search & Ranking Models, Deep Learning, NLP, LLMs, Causal Inference, Reinforcement Learning, Multi-Armed Bandits, and Model Optimization.
• Experience across the complete ML lifecycle, including feature engineering, training pipelines, model validation, deployment, monitoring, and continuous improvement.
• Experience working with large-scale datasets and distributed computing frameworks.
• Good understanding of MLOps concepts, scalable ML architectures, and production ML systems.
• Strong analytical thinking, problem-solving abilities, communication skills, and cross-functional stakeholder collaboration experience.

• Experience working on personalization, customer growth, advertising, content recommendation, or large-scale consumer platforms.
• Exposure to cloud-based ML platforms and production ML infrastructure.
• Knowledge of modern AI/GenAI tools and frameworks.
• Ability to translate research concepts into practical business solutions.

• A Great Place to work
• Equal opportunity employer
• Fast track growth opportunities