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.

We are looking for a talented Senior Data Scientist with strong statistics and causal inference experience to help us understand how content promotion and personalization algorithms come together. The distribution and promotion of our content as well as personalization are key to how members discover and choose content they would enjoy.

As a Senior Data Scientist, you’ll partner with the business leaders responsible for content & product promotion, Product and Algorithms engineering teams and other diverse stakeholders across the business to shape strategy and deliver impact through analytics, experiments, statistical learning and other causal inference methods. 

In this role, you will:

Leverage causal inference methods or statistically sound analyses to drive actionable insights and help shape our understanding of how product, content and algorithms influence member experience.

Build metrics and measurement frameworks that are statistically and causally robust to empower decision-making for stakeholders and product features that can deliver member joy.

Establish strong partnerships with team members and diverse stakeholders across the business.

Facilitate ownership and accountability by ensuring that the team is producing trustworthy and high-quality outputs that influence the decisions and direction of a variety of areas of Netflix.

Proactively explore trends in member engagement to surface future opportunities.

Work independently and drive your own projects.

To be successful in this role, you have:

An advanced degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.

5+ years of relevant experience in one or more data science roles.

Expertise in statistical analysis methods, most notably regression analysis, causal inference, statistical learning and experimentation methods.

Strong data manipulation and quantitative programming skills in SQL, R and/or Python.

Exceptional communication with technical and non-technical audiences; highly effective at developing meaningful stakeholder relationships and deep domain expertise.

Comfort with ambiguity; ability to thrive with minimal oversight and process.

Embodies the Netflix values while bringing a new perspective to continue improving our culture.

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 $170,000 - $720,000.

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. 

Inclusion 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.