Senior Machine Learning Manager, Content ML

Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

At Netflix, we seek to entertain the world. We launch thousands of new TV shows and movies every year for our members across the globe and we need to understand which shows to launch when, for which audiences over the next months, quarters and years to delight our current members and bring in new ones. We seek to empower our creative and strategy teams to build the best possible slate of content for the future by understanding what both our members and non-members want.  As Netflix continues to evolve, this increasingly includes new content formats (like our new live offering), and new audiences.

Given this ambitious goal, we are looking for a seasoned technical leader to manage the team of Machine Learning Scientists who work closely with our creative, finance, and strategy teams to help build models that will support content valuation, scheduling and programming by forecasting what content people are likely to watch and talk about over time.

What you will do in this role:

• Oversee and evolve a suite of content forecasting models to help us understand how our, and our competitors' content is likely to perform over time.

• Understand the interactions between content and various signals of social buzz on the value of Netflix’s catalog.

• Work closely with partner teams to develop usable decision frameworks that leverage these insights to make our content slate better over time

• Hire, inspire, and grow high-performing team members

• Lead innovation at Netflix by leveraging the right state-of-the-art methods in machine learning and statistical inference to solve business problems

This role is for you if:

• You have a proven track record of applying machine learning with industrial scale data 

• You excel at thinking through a business problem and solving it by leveraging data, you can then translate those solutions into compelling narratives to help drive adoption.

• You are flexible and able to adapt to a rapidly changing environment –  you build teams who can do the same. You embrace risk and are willing to make hard calls and pivot as needed.

• You have deep technical expertise in a variety of modelling approaches including time series, observational causal inference, reinforcement learning and forecasting approaches.  This expertise is coupled with the ability to examine tradeoffs amongst potential solutions in order to optimize outcomes for the business.  You know how to use a complicated model, but you also know when a linear regression is best.

• You enjoy connecting the dots across a variety of groups and problems, and you enjoy fostering collaborative relationships as much as you enjoy driving deep technical solutions.

• You have a PhD/MS degree in a quantitative field like Operations Research, Economics, or Computer Science and have 10 years of industry experience with at least 3 years of managerial experience.

Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $480,000 - $1,200,000.

is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.