Netflix is one of the world’s leading entertainment services with 278 million paid memberships in over 190 countries enjoying TV series, films, and games across various genres and languages. Members can play, pause, and resume watching as much as they want, anytime, anywhere, and change their plans anytime.
The Role
With over a quarter billion members in over 190 countries and a billion hours of monthly streaming, Netflix is the world’s leading online entertainment company. Netflix continues to shape the future of entertainment by developing personalized ways for members to discover and enjoy a rapidly expanding catalog of content.
The Machine Learning & Inference Research (MLIR) team works on core methodological development in areas of strategic importance to Netflix and translates this research into actionable impact by partnering with other teams (e.g. data science, engineering, design, product). MLIR engages with the external research community spanning ML/AI, statistics, economics, and operations research through conferences, academic collaborations, and publications. At the same time, it engages with the internal Netflix community by disseminating research learnings, advising on the incorporation and practical implementation/scalability of new methods and technologies, and partnering on translational applied research with a direct impact on Netflix product and content priorities. In success, the MLIR team’s expertise and foundational research influence and steer a growing number of projects and roadmaps and cultivate and advance in-house world-class expertise.
What you’ll do
We are seeking an experienced leader to define and execute a strategy that brings cutting-edge methods and holistic thinking to Netflix. The leader must balance a portfolio of foundational/methodological developments spearheaded by the team and collaborative projects with stakeholder teams that directly benefit from these developments. Such collaborations span applied research (such as exploring innovations to the member experience or analyzing Netflix data for actionable insights), devising ambitious yet technically feasible innovation roadmaps, and helping craft technical approaches to advance these roadmaps. To be successful, the leader must be deeply familiar with the business needs, adept at translating these needs into a long-term research agenda, galvanize other teams around this agenda, and be committed to fostering an open environment of collaboration, innovation, and intellectual excitement.
Specifically, you will:
- Inspire and lead a senior team of research scientists to shape machine learning and causal inference excellence at Netflix.
- Work closely with a wide range of partners (scientists, engineers, designers, product managers, finance/strategy, etc.) to maintain a strong portfolio of projects that impact our members and our business, often in collaboration with business-domain data science and engineering teams.
- Uplevel our research best practices and our organizational expertise in machine learning and causal inference and the latest developments therein.
- Help prioritize and balance competing priorities for the long-term benefit of Netflix
- Be a leader and role model within the Data & Insights team, including enriching Netflix’s broader machine learning & experimentation community.
- Build a successful and highly productive research program that includes research scientists, external academic collaborations, and research interns.
- Boost the visibility of Netflix research through research products such as external presentations and publications aligned with Netflix’s interests in top-tier venues and by forming connections with academic labs and researchers.
We’re looking for
- You have made meaningful impacts and brought clarity to complex or ambiguous technical problem spaces. You exhibit excellent judgment in developing a portfolio of high-risk/high-reward, long-term projects and leading a team to execute them.
- You possess outstanding oral and written communication skills that resonate within and beyond your team. You have a proven track record as a trusted partner to both technical and business stakeholders.
- You have successfully operated in a company where collaboration and integration with other teams across multiple disciplines are essential to your team’s success.
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- You are pragmatic and maximize impact through careful consideration of the trade-offs that business-domain teams must make.
- You have experience and demonstrated success in building and leading a research program, in retaining high-caliber applied research teams, and in fostering an inclusive team culture.
- You have proven experience moving the business forward, uplifting the broader team and orchestrating thought leadership that raises the bar for the organization.
- You have a Ph.D. in a quantitative field such as Mathematics, Computer Science, Statistics, Physics, Operations Research, Economics, etc.
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 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 $610,000 – $1,870,000.
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.
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 based on 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.
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