Senior Data Scientist - Content Valuation and Programming

Job Description

Location: Los Angeles (preferred); or Los Gatos.

Netflix has entered a completely new phase of its evolution. We are combining the worlds of technology and entertainment, with 180+ million global members and over 1000 original shows and films from around the world. We face the dual challenge of successfully launching more shows than any studio in history, and doing so in a personalized manner to the largest audience (current + future members).
Our data-driven culture allows us to innovate to provide the best catalog offering for our current and future members to maximize their satisfaction and drive acquisition.

The Content Programming and Valuation Data Science and Engineering (''DSE'') team is at the forefront of advancing analytic methods and products to improve programming - what content to add to the Netflix catalog and how to allocate budget to buy that content. In close collaboration with business and content leaders, the team is working to revolutionize how we use data to inform and aid strategic business decisions in content prioritization, portfolio optimization, and value measurement. We drive considerable business impact through strong partnerships and relentless commitment to practical methodological innovation and application. Example areas include supervised machine learning, observational causal inference modeling to understand substitution and content demand, incremental value measurement, and member and non-member preference analyses.

While our approaches and impact are industry-leading, we are just scratching the surface of the potential given the complexity of the entertainment industry and the scale of our business. Near term, we need to apply our methods advancements to existing business questions, and long term help define and prioritize future business problems. To achieve this potential, we need a Senior Data Scientist who is cross-functional, humble, innovative, and deep in observational causal inference, modeling, and product sense to help lead and scale data, reporting, and modeling.

To learn more about our research and analytics work, you can visit our research page.

Responsibilities
• Partner with creative and strategy partners to design actionable and insightful analyses to guide future content decisions
• Improve our understanding of content value by developing and maintaining observational causal inference models
• Collaborate on software development with other scientists and engineers to enable and accelerate model innovation and impact
• Drive innovation by developing new methodologies, statistical techniques, and causal-inference approaches that could sharpen our content decision-making process.
• Research new measurements and frameworks to enable understanding of emergent phenomena, e.g. the impact of off-product behavior on Netflix viewing.
• Ownership of stakeholder relationship and end-to-end delivery of actionable insights for decision makers and effective integration with systems

Qualifications
• 5+ years of experience driving business impact through rigorous reasoning and analysis
• PhD in a quantitative field (e.g., Computer Science, statistics, social or natural science), or other advanced degree with additional experience
• Proven record in setting and executing analytic plans to meet business priorities
• Deep experience in applied data analysis, including A/B testing and observational causal inference methods
• Experience prototyping and productizing ML models in a mature software environment
• Strong programming skills in Python or R
• Experience with distributed analytic processing technologies (e.g., Spark, Presto)
• Exceptional interpersonal and communication skills
• A fan of Netflix is a strong plus

A few more things to know
• Our culture makes us better, and we take it seriously. Please check out our unique culture to understand if our values resonate: Netflix Culture
• We are a tight team with big goals - so we seek individuals who are collaborative and passionate. We support a balanced lifestyle to preserve this team culture.

Jobcode: Reference SBJ-gww82g-3-144-113-197-42 in your application.