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+. They specialize in applying machine learning methods to meet strategic product personalization goals, explore innovative techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes. As a member of this team you will collaborate across Engineering, Product, and Data teams to better understand challenges and develop automated solutions to be built into our products.
Responsibilities :

• Algorithm development and maintenance: Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams
• Analysis and Algorithm Optimization: Perform deep dive analysis on app interactions and user profiles as they relate to algorithm output in order to drive improvements in key personalization metrics
• Data Preparation: Process, cleanse, and verify the integrity of data used for model building, experimentation evaluation, and algorithm performance
• MVP development: Develop innovative data science products to be used for new production features or downstream by production algorithms
• Development Best Practices: Maintain existing and establish new algorithm development, testing, and deployment standards
• Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve how we do data collection, experimentation and analysis

Basic Qualifications :

• 4+ years of experience developing machine learning models and performing data analysis with Python or R
• 3+ years writing production-level, scalable code (e.g. Python, Scala)
• 3+ years of experience developing algorithms for deployment to production systems
• In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings
• In-depth understanding of the latest in natural language processing techniques and contextualized word embedding models
• 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:

• Production experience with developing content recommendation algorithms at scale
• Production experience with graph based models (e.g. node2vec)
• Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, regression testing, 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

Required Education :

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

Additional Information :
Location:

• New York, NY (preferred) or Remote

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