Staff, Data Scientist

Your New Role:
This position will join the Enterprise Data and AI team that supports all brands in the Warner Bros umbrella including WB films in theatrical and home entertainment, DC studios, Consumer Products, games, etc. The ideal candidate is a subject matter expert in data science with exposure to predictive modeling, forecasting, recommendation engines and data analytics. This person will build data pipelines, apply statistical modeling and machine learning, and deliver meaningful insights about customers, products and business strategy WBD to drive data-based decisions

As a Staff Data Scientist, you will play a critical role in advancing data-driven solutions to complex business challenges, influencing data strategy efforts for WBD Businesses. The responsibilities include:

• Analyze complex, high volumes of data from various sources using various tools and data analytics techniques.

• Partner with stakeholders to understand business questions and provide answers using the most appropriate mathematical techniques.

• Model Development and Implementation: Design, develop, and implement statistical models, predictive models and machine learning algorithms that inform strategic decisions across various business units.

• Exploratory Data Analysis: Utilize exploratory data analysis techniques to identify and investigate new opportunities through innovative analytical and engineering methods.

• Advanced Analytics Solutions: Collaborate with Product and Business stakeholders to understand business challenges and develop sophisticated analytical solutions.

• Data Automation: Advance automation initiatives that reduce the time spent on data preparation, enabling more focus on strategic analysis.

• Innovative Frameworks Construction: Develop and enhance frameworks that improve productivity and are intuitive for adoption across other data teams and be abreast with innovative machine learning techniques (e.g., deep learning, reinforcement learning, ensemble methods) and emerging AI technologies to stay ahead of industry trends.

• Collaborate with data engineering teams to architect and scale robust, efficient data pipelines capable of handling large, complex datasets, ensuring the smooth and automated flow of data from raw collection to insights generation.

• Deployment of machine learning models into production environments, collaborating with DevOps and engineering teams to ensure smooth integration and scalability.

• Quality Assurance: Implement robust systems to detect, alert, and rectify data anomalies.

Qualifications & Experiences:

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

• 8+ 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 advanced statistical techniques and concepts (regressions, statistical tests etc.) and experience with application of these tools.

• A demonstrated track record of utilizing data science to solve business problems in a professional environment.

• 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.

• Strong analytical and problem-solving abilities.

• Excellent communication skills to effectively convey complex data-driven insights to stakeholders.

• High attention to detail and capability to work independently in managing multiple priorities under tight deadlines.

• Proficiency in big data technologies (e.g., Spark, Kafka, Hive).

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

• Ability to collaborate effectively with business partners and develop and maintain productive professional relationships.

• Experience with adhering to established data management practices and standards.

• Ability to communicate to all levels of business, prioritize and manage assignments to meet deadlines and establish strong relationships.

• Interest in movies, games, and comics is a plus.