Netflix is revolutionizing the entertainment industry with world-class technology. We are both a content distributor and a producer for original shows, serving millions of subscribers worldwide in more than 190 countries around the world. We produce hundreds of new series, movies, documentaries, stand-up specials and other categories of content 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, transcending geographical and cultural borders.
The Content Demand Modeling team, within the Data Science & Engineering org, is founded on the premise that empowering creative executives and content decision makers with data-driven insights using statistical analyses and machine learning will provide a significant competitive advantage to Netflix. Analytics play a critical role in developing metrics that allow us to better understand the total audience and value of movies and TV shows (to Netflix). Through analytics and ML modeling, we aim to channel how our global member base engages with our content, and surface key elements that contribute to the success of stories on Netflix.
As a Senior Analytics Engineer in this space, you will…
• Be entrepreneurial and collaborative with business partners (for example, content planning and analysis teams) to define critical analytical problems and find innovative solutions with data
• Independently deliver effective solutions to problems
• Provide insight and influence content decision-making through development of tools, metrics and dashboards
• Partner closely with applied machine learning scientists & engineers on the team to support exploratory feature discovery, extracting useful & actionable macro insights
• Partner closely with Data Engineers to source data from new systems and stand up lightweight pipelines as needed to drive impact
• Be a thought leader in defining the vision for what analytical tooling can and should do in the space to drive the most impact
Examples of questions you will help to answer (not an exhaustive list!):
• Talent (e.g. actor, writer, director) & source IP (e.g. books, comics, video games) are crucial building blocks of a story. How can we develop a set of useful metrics & features to predict title performance - both globally and by region?
• Similarly, for source IP, are there metrics that can capture the adaptation potential of a published book? Which books have the potential to turn into franchises?
• Machine Learning models can be opaque. Their black box nature can sometimes limit trust in them. Our team owns & develops a family of content demand prediction models. Leveraging state of the art techniques, can we develop methods & tools that allow our engineers and business partners alike to better interpret and build intuition around model behavior and outputs?
• Development of new signals that improve our models through exploratory data analyses; evaluating high-level hypotheses from our stakeholder teams, validating and iterating on these hypotheses to develop useful metrics and spinning up dashboards where appropriate.
• Scripts are a rich source of information very early in a movie or TV show's lifecycle - when relatively little else is known. How can we better surface useful information from scripts (Who are the key characters? How do they interact? etc)
• A senior analytics professional with a proven track record of data wrangling, analysis, reporting & visualization
• An expert in a data-oriented programming language/ETL (e.g. SQL, Python) and comfortable with data visualization tools (e.g. Tableau) & analytics software (e.g. ElasticSearch)
• Familiar with core statistical concepts and applied modeling techniques (e.g. quantiles, sampling methods, hypothesis testing, regression, clustering)
• A strong communicator who can own and deepen direct relationships with stakeholders and business partners
• Enthusiastic about innovating in a fast-moving data and analytics space
• Passion for and an appreciation of the entertainment industry a plus
Jobcode: Reference SBJ-d587j1-54-174-225-82-42 in your application.