Manager, Machine Learning - Studio Intelligence

At Netflix, our mission is to entertain the world by connecting our members to an extensive library of amazing stories from all over the globe. We are revolutionizing storytelling as we deliver content to 260+ million members across 190+ countries in 30+ languages. Developing data-driven methods and systems to help Netflix teams plan and manage the operations supporting content production is a critical part of that mission. 

We're looking for a Manager to lead the Studio IntelligenceMachine Learning team. This talented team operates at the heart of Netflix's business: helping Content and Studio functions forecast and plan our content financials and scheduling. This work informs decision-making on investments for new original shows. We develop new data sets and pipelines, deliver analytic tools, conduct statistical analyses, and build Machine Learning models, all with the goal of helping our creative teams produce the best shows and movies.

In this role, you will:

• Lead and mentor a group of Data Scientists and Analytics Engineers with diverse skill sets that cut across statistics, Machine Learning, analytics, and data engineering
• Craft and evolve a strategic vision for research and implementation of forecasting algorithms and analytics in content planning
• Identify, explore, and own new, creative applications of data science and Machine Learning across Content Operations workflows
• Establish and maintain strong partnerships with business stakeholders, working directly with them to introduce and influence data-informed ways of working
• Collaborate with other Data Science and Engineering teams to uplevel our foundational data models and data health   
• Partner with Product and Engineering teams to develop holistic technical solutions for Content Finance, Content Planning, and Content Production business teams

The ideal candidate will have:

• Multiple years of experience building and managing high-performing data science teams; a demonstrated track record of driving innovation and shaping business strategy with data 
• A self-starter mindset; a high degree of comfort working amidst ambiguity and leading in a fast-paced environment 
• A passion for people leadership: you are energized by hiring, coaching, and investing in your team members 
• A background working as a hands-on individual technical contributor in a data field: Machine Learning, statistics, operations research, or data science, as examples
• Familiarity with deploying data science solutions into production environments and comfort partnering closely with Engineering teams 
• Exceptional written and verbal communication skills, able to act as the bridge between technical and non-technical audiences

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 $360,000 - $920,000.  

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs.  Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more detail about our Benefits here .

Netflix is a unique culture and environment.  Learn more here .

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, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.