The Walt Disney Company (Germany) GmbH
Manager Data Science
The Walt Disney Company (Germany) GmbH, Snowflake, Arizona, United States, 85937
About The Role
The Commerce Data Science team at Disney Streaming develops Machine learning solutions to drive subscription and monetization across our streaming platforms, including Disney+, Hulu, and ESPN+. Data scientists are integral to Disney’s success, partnering with cross-functional teams (growth, content, marketing, product, and engineering) to provide ML solutions that shape the experience of millions of users worldwide.We're seeking an experienced Manager of Data Science to lead data scientists focused on developing and deploying machine learning models that address business-critical challenges. In this role, you’ll work with teams across commerce, growth, and identity to leverage machine learning solutions that enhance the customer journey and drive the business forward.Responsibilities
Lead Machine Learning InitiativesDesign, build, and optimize machine learning models that optimize commerce payment products.
Manage the full lifecycle of ML development, including data collection, feature engineering, model selection, evaluation, and production.
Collaborate with engineers to deploy models at scale, ensuring robust A/B testing frameworks to assess the impact on key business metrics.
Data Exploration & InsightsDive deep into subscriber and payment data to uncover patterns and opportunities for growth and retention strategies.
Lead exploratory analyses and complex statistical modeling to deliver actionable insights that inform high-stakes business decisions.
Data StorytellingTranslate complex data into clear and actionable insights through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders.
Drive data-informed decision-making by presenting findings that highlight business implications.
Strategic Collaboration & LeadershipBuild and foster strong relationships with business partners across commerce, growth, marketing, and engineering.
Collaborate with other data teams to improve our data infrastructure, including models, visualizations, and experimentation capabilities.
Mentor and grow a high-performing team of data scientists, creating an environment that encourages learning and innovation.
Basic Qualifications
Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field of study.
Proven track record of working with programming languages (e.g., Python, Spark, PySpark) and SQL.
Expertise in ML libraries such as scikit-learn, SciPy, and related technologies.
Experience with modern data platforms and tools (e.g., Databricks, Jupyter, Snowflake, Airflow, GitHub).
Advanced statistical knowledge and excellent problem-solving skills, with a proven ability to translate data into actionable insights.
8+ years of experience in building, deploying, and evaluating real-world machine learning solutions.
2+ years of leadership experience.
Preferred Qualifications
M.S. and/or Ph.D. in a quantitative discipline.
Experience working in subscription-based or streaming media businesses.
Additional Information
#DISNEYTECH
#J-18808-Ljbffr
The Commerce Data Science team at Disney Streaming develops Machine learning solutions to drive subscription and monetization across our streaming platforms, including Disney+, Hulu, and ESPN+. Data scientists are integral to Disney’s success, partnering with cross-functional teams (growth, content, marketing, product, and engineering) to provide ML solutions that shape the experience of millions of users worldwide.We're seeking an experienced Manager of Data Science to lead data scientists focused on developing and deploying machine learning models that address business-critical challenges. In this role, you’ll work with teams across commerce, growth, and identity to leverage machine learning solutions that enhance the customer journey and drive the business forward.Responsibilities
Lead Machine Learning InitiativesDesign, build, and optimize machine learning models that optimize commerce payment products.
Manage the full lifecycle of ML development, including data collection, feature engineering, model selection, evaluation, and production.
Collaborate with engineers to deploy models at scale, ensuring robust A/B testing frameworks to assess the impact on key business metrics.
Data Exploration & InsightsDive deep into subscriber and payment data to uncover patterns and opportunities for growth and retention strategies.
Lead exploratory analyses and complex statistical modeling to deliver actionable insights that inform high-stakes business decisions.
Data StorytellingTranslate complex data into clear and actionable insights through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders.
Drive data-informed decision-making by presenting findings that highlight business implications.
Strategic Collaboration & LeadershipBuild and foster strong relationships with business partners across commerce, growth, marketing, and engineering.
Collaborate with other data teams to improve our data infrastructure, including models, visualizations, and experimentation capabilities.
Mentor and grow a high-performing team of data scientists, creating an environment that encourages learning and innovation.
Basic Qualifications
Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field of study.
Proven track record of working with programming languages (e.g., Python, Spark, PySpark) and SQL.
Expertise in ML libraries such as scikit-learn, SciPy, and related technologies.
Experience with modern data platforms and tools (e.g., Databricks, Jupyter, Snowflake, Airflow, GitHub).
Advanced statistical knowledge and excellent problem-solving skills, with a proven ability to translate data into actionable insights.
8+ years of experience in building, deploying, and evaluating real-world machine learning solutions.
2+ years of leadership experience.
Preferred Qualifications
M.S. and/or Ph.D. in a quantitative discipline.
Experience working in subscription-based or streaming media businesses.
Additional Information
#DISNEYTECH
#J-18808-Ljbffr