Job Summary:

The Team:

Disney Media and Entertainment Distribution’s mission (DMED) is to delight consumers around the world with the entertainment and sports content they want most, with more choice, personalization, and convenience than ever before.
Comprised of Disney’s International media businesses and the Company’s streaming and linear services, the DMED Engineering segment aligns technology, content and distribution platforms to expand the Company’s global footprint and deliver world-class, personalized entertainment experiences to consumers around the world.
DMED is responsible for The Walt Disney Company’s direct-to-consumer businesses globally, including the ESPN+ sports streaming service, programmed in conjunction with ESPN; Disney+, the Disney-branded direct-to-consumer streaming service; global advertising sales and ad technology for all of Disney’s media properties, including ABC, ESPN, Freeform, FX Networks, National Geographic and the Disney Channels; HotStar, the leading over-the-top streaming service in India; and the Company’s majority ownership stake in Hulu.

Job Overview :

We are looking for a Senior Data Scientist to join our newly created Data & Intelligence team in the DMED Technology’s Content Platforms group.

The data scientist will join a team of engineers and product managers to deliver the world’s most innovative, automated, and technologically advanced content platform through the integration of predictive models and analytical insight.

The core contributions of the Senior Data Scientist will consist of technically define problems gathered from stakeholders, define experimentation setups, research data driven solutions to the problems identified, provide technical mentorship to other data scientists and communicate results to stakeholders.

Responsibilities :

• Serve as a technical and leadership mentor to the team. Encourage and set the example for collaboration across functions. Forge solid relationships with peers in other disciplines.

• Design and implement models and methodologies on variety of datasets to achieve operational excellence and personalization efforts for our digital product lineup

• Make strategic recommendations on data collection, integration and retention incorporating business requirements and knowledge of best practices.

• Become and stay an expert in current and emerging technologies and tools.

Basic Qualifications :

• Proven excellence in leading and contributing to Data Science projects in a commercial setting

• Proven track (patents, publications) of pushing state of the art in the data science / machine learning space.

• Strong communication, interpersonal skills and fortitude to get stuff done

• Experience in leading discovery processes with stakeholders to identify the business requirements and the expected outcome

• Capability to educate the organization both from technical and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results

• Proven experience providing technical mentorship to junior team members

• Demonstrate the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, fairness and aptitude for original research 

• Comfortable working in a team environment using Agile methodologies

• Expert level in machine learning architecture and model development, ideally contributing to one of the main machine learning frameworks.

• Up to date knowledge on PyTorch and packages in its ecosystem (3+ years)

• Strong working knowledge of statistical frameworks (Pandas, NumPy/SciPy, scikit-learn) (5+ years)

• Strong working knowledge of machine learning frameworks (PyTorch, TensorFlow) (5+ years)

• Mastery in at least one high-level programming language such as Python or Scala (7+ years)

• Expert level in advanced analytic and statistical modeling

• Experience monitoring the full life cycle of models

• Mastery in SQL and experience with NoSQL databases

• Experience with human-in-the-loop machine learning solutions

• Experience with cloud platforms such as AWS, Google Cloud, Azure

• Experience with Docker

• Experience with ETL pipelines

Preferred Qualifications :

• Experience with distributed processing relevant technologies like Kafka and Hadoop

• Experience crafting visualization tools

• Media Industry experience

Required Education :

• M.S. degree in the fields of Economics, Analytics, Mathematics, Computer Science, Statistics, Machine Learning, or other quantitative fields

Preferred Education :

• Ph.D. in the fields of Economics, Analytics, Mathematics, Computer Science, Statistics, Machine Learning, or other quantitative fields