Applied Machine Learning Engineers and Data Scientists on the Disney Streaming Machine Learning and Innovation team develop and maintain recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will help build and manage a team that works across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
Responsibilities :
We are looking for a Manager of Applied Machine Learning Engineering who can attract and retain diverse engineering and data science talent, drive a culture of ownership and excellence, and be responsible for the development of cutting edge recommendation and personalization algorithms and model evaluation platforms. You will be required to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams, and expected to help meet KPIs for product areas and to set and meet deadlines for external and internally facing tools, such as offline evaluation tools for pre-production algorithms. As a leader in the area of content recommendation and personalization, you will also be responsible for helping to set the roadmap for algorithmic work, and for driving larger company objectives in the areas of personalization and content recommendation.
Basic Qualifications :

• 5+ years of engineering experience and/or 5+ years of experience in machine learning development (e.g. algorithm development, machine learning engineering)
• 2+ years engineering or data science management experience
• In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings
• Experience with cloud services in a production environment (particularly AWS)
• Familiarity with data exploration and data visualization tools like Tableau, Looker, Chartio, etc.
• Understanding of statistical concepts (e.g., hypothesis testing, regression analysis)
• Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate
• Strong written and verbal communication skills
• Ability to explain how models are used and algorithms behave to both technical and non-technical audiences

Preferred Qualifications:

• Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment
• Experience with graph-based data workflows such as Apache Airflow
• Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks
• Familiar with metadata management, data lineage, and principles of data governance
• Experience loading and querying cloud-hosted databases such as Snowflake
• Building streaming data pipelines using Kafka, Spark, or Flink
• Familiarity with automated deployment, AWS infrastructure, Docker or similar containers
• Production experience with developing content recommendation algorithms at scale

Preferred Education :

• MS or PhD in statistics, math, computer science, social science, or related quantitative field

Additional Information :
Location - New York, NY preferred but also open to US Remote for the right candidate
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