Senior Data Scientist

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:
As a Sr. Data Scientist, you will be responsible for analyzing large and complex datasets from diverse sources, including movies, gaming, studios, and enterprise operations. You will leverage statistical modeling, machine learning, and data visualization techniques to uncover valuable insights that drive decision-making in content development, marketing strategies, audience targeting, and enterprise-level functions such as finance, operations, and customer experience. Your work will support both creative and business teams in delivering data-driven strategies and maximizing the impact of our products and services.

Your Responsibilities:

Model Building & Training:

• Design, build, and validate machine learning models to predict key business outcomes such as user engagement, content performance (e.g., box office, streaming views), and customer retention in gaming platforms.

• Utilize supervised and unsupervised learning techniques, including regression models, classification algorithms, clustering, recommendation systems, and time series forecasting, to address business needs.

• Implement deep learning techniques, including neural networks and natural language processing (NLP) for advanced content analysis and user behavior prediction.

• Deploy machine learning models into production environments, working closely with DevOps or engineering teams to ensure seamless integration into operational workflows.

• Continuously monitor model performance and refine models based on feedback and evolving data.

• Optimize models for efficiency, scalability, and accuracy, using advanced techniques like hyperparameter tuning, cross-validation, and model assembling.

• Collaborate with data engineers to build and maintain efficient data pipelines for preprocessing large-scale datasets.

• Automate data collection, cleaning, and feature engineering processes to ensure timely and accurate data for model building.

• Bachelor's degree, MS, or greater in Computer/Data Science, Engineering, Mathematics, Statistics, or related quantitative discipline.

• 5+ years relevant experience in Data Science.

• Expertise in a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, random forests, deep learning etc.) and experience with applications of these techniques.

• Expertise in SQL and either Python or R, including experience with application deployment packages like R, Streamlit or Shiny.

• Experience with database technologies such as Databricks, Snowflake, and others.

• Familiarity with BI tools (Power BI, Looker, Tableau) and experience managing workflows in an Agile environment.
• Proficiency in big data technologies (e.g., Spark, Kafka, Hive).

• Experience working in a cloud environment (AWS, Azure, GCP) to facilitate data solutions.