The Role

With nearly 200 million members in over 190 countries and a billion hours of streaming each month, Netflix is the world’s leading online entertainment company. 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 & 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. 

We are looking for an exceptional machine learning leader to manage a team of stunning machine learning scientists and engineers that own and innovate upon a suite of high-visibility ML models. These models offer key content metric predictions at all stages in a title’s lifecycle and are leveraged by a broad set of stakeholders across the company to inform a variety of content decisions from planning our slate to production execution to post-launch evaluation and renewals.

Responsibilities

• Lead a team of applied machine learning scientists and provide technical guidance and mentorship to members of the team.
• Drive the vision and shape the roadmap of content prediction models, thoughtfully balancing the needs of multiple business stakeholder teams.
• Amplify the impact of the team and foster trust in model-driven outputs from content strategy & creative stakeholder teams. 
• Understand and work backwards from the needs, workflows, and decision points of content creators in shaping the team’s roadmap and outputs. 
• Be a strategic thought partner for the Content, Strategy & Analysis teams, in identifying opportunities for impact from content prediction models.
• Manage high-quality and robust production-level machine learning models in a rapidly evolving business environment.
• Collaborate effectively and influence roadmaps of partner data science & engineering teams.
• Enact Netflix values in daily work and interactions.

Who Will be Successful in this Role

• In order to be successful in this position, you will need 1) business acumen to understand how data-driven approaches can effectively influence creative decisions (effective bridges between art & science), 2) to collaborate effectively with a broad and complex set of partners and stakeholders across the company and 3) technical acumen to mentor and grow top-notch applied ML individual contributors.

Specific qualifications include:

• Demonstrated experience in building, managing, mentoring, and inspiring applied science teams, with a proven track record of leveraging machine learning to drive impact.
• Exceptional interpersonal and communication skills, including proven ability to effectively collaborate with a variety of technical and non-technical  business partners and other data science leaders. 
• PhD in Statistics, Computer Science, Machine Learning, Mathematics, or related field.
• Experience in developing, prototyping, and deploying machine learning models.
• High-energy self-starter with a passion for business impact through data science (especially machine learning), tolerance for ambiguity in a fast-paced setting, and a positive attitude.

To learn more about Netflix research, check out the Netflix Research website.

Culture

You will have the opportunity to impact the business in a meaningful way. You will have the freedom to innovate, solve interesting problems and influence in a fast paced, exciting environment. You will work with stunning colleagues who love to solve hard problems, and who not only expect but also foster high performance. You can learn more about Netflix culture at jobs.netflix.com/culture. 

We are an equal opportunity employer and celebrate diversity, recognizing that diversity of thought and background builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.