Netflix is revolutionizing the entertainment industry with world-class technology. We are both a content distributor and a producer for original and premium shows. We serve millions of subscribers in more than 190 countries around the world. We produce hundreds of new series, movies, documentaries, stand-up specials, and content across various other categories each year. Because of our global footprint, we are able to elevate new types of creators, tell a diverse set of stories and inspire a global audience.
The Content Demand Modeling team, within Data Science and Engineering, plays a central role in informing and supporting content decisions. Arming our creative teams with data-driven insights improves both the efficiency and accuracy of decision-making and helps Netflix produce more hits and create more member joy at better economics. Our shared mission is to scale decision-making, opportunity detection, and discovery for creative exploration.
The team consists of a mix of machine learning scientists (ML) and ML engineers. Our portfolio of projects ranges from production ML models that we support and innovate upon, to longer term research projects with potential game-changing impact. Additionally, because our models inform content decisions, there is an emphasis on interpretability and user trust.
We would like to bring on board a machine learning data scientist with strong engineering skills. As a member of this team, you will conduct applied research by investigating, conceptualizing, designing, implementing and validating new algorithms in the area of forecasting content demand. You will also contribute to the development of shared ML infrastructure that allows the team to more effectively scale impact.
Questions You Will Help Answer
· Which subscribers will this title resonate with? How many are likely to watch it?
· What other titles on our service are comparable to this one?
· To what extent do we expect this title to travel outside its local market?
· Can we identify potential hits in advance and determine what makes a hit?
· What are all the unique content tastes across our large and diverse member base?
· End-to-end development of machine learning models that will have a high-impact on our decision-making.
· Be entrepreneurial and collaborate with business partners to identify potential high-value applications of machine learning technology to our domain.
· 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.
· Synthesize common patterns & build effective abstractions across different ML pipelines that accelerate the impact of ML driven insights.
· Enact Netflix values in daily work and interactions.
· At least four years of applied ML experience with a successful track record of delivering quality results.
· Solid experience in building production machine learning systems.
· Excellent communication skills and an ability to translate business context and intuition into data-oriented hypotheses to drive impact.
· Experience building robust ML infrastructure, applying engineering best practices.
· Strong coding experience. Experience with open-source ML packages (specifically sklearn, TensorFlow/Keras/PyTorch).
· Passion for and an appreciation of the creative and entertainment industry is definitely a plus.