Senior Applied Machine Learning Scientist - Content Machine Learning
Netflix, Los Angeles, California
Leading subscription service for watching TV episodes and movies
Examples of Questions you will help to answer (not an exhaustive list):
- Forecasting audience sizes for specific content and how that prediction should inform its valuation and other major business decisions.
- Estimating the acquisition potential of specific content -- what type of content draws audiences to sign up for our service.
- What are the dimensions along which content is cultural or local vs. universal? How can we translate this information into better demand forecasting models for specific content categories, e.g., anime in Japan?
- Opportunity detection -- helping our stakeholders cultivate potential hits in advance and identifying the components that might make them successful.
- How can we understand the mechanics through which various elements that constitute the entertainment space result in its success (or not)?
- In short, our shared mission is to scale decision-making, opportunity detection and discovery for creative exploration.
- Develop machine learning models that will have high-impact on our decision-making.
- Be entrepreneurial and collaborate with business partners (for example, content planning and analysis team) to identify potential high-value applications of machine learning technology to content demand prediction, valuation and opportunity discovery
- Communicate results to a variety of audiences, technical and non-technical.
- Independently deliver effective solutions to problems.
- Own full-stack technology, from data to product and the feedback loop.
- Enact Netflix values in daily work and interactions.
- At least three years of applied ML experience with a successful track record of delivering quality results.
- Solid experience in developing learning methodologies and building robust production machine learning systems.
- Excellent communication skills and an innate ability to translate business context and intuition into data-oriented hypotheses to drive impact.
- Strong coding experience. Experience with open-source ML packages (specifically sklearn, TensorFlow/Keras/PyTorch).
- Desire and willingness to continue growing your capabilities as a ML scientist in innovating modeling and algorithms.
- Passion for and an appreciation of the creative and entertainment industry is definitely a plus.
Netflix is the world’s leading Internet television network with over 100 million members in over 190 countries enjoying more than 125 million hours of TV shows and movies per day, including original series, documentaries and feature films. Members can watch as much as they want, anytime, anywhere, on nearly any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.
Want to learn more about Netflix? Visit Netflix's website.
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