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 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.

The Role

We are seeking a Senior Data Scientist with strong machine learning and causal inference experience to lead algo evaluation and explainability. Our algos cover a wide range of modeling techniques from boosted trees to neural networks, including deep networks and LLMs. In this role, you will develop methods and models to explain why our product promotes or doesn’t, a given title to a member. Working in a highly collaborative and cross-functional environment, you will be responsible for partnering with our Product and Algo Engineering teams to develop a deep understanding of our algo systems and generate robust methodologies that answer the “why” behind product recommendations.

As a Senior Data Scientist, you’ll be at the forefront of recommender systems and product innovation. You’ll work across teams of data scientists, algorithm engineers, and product stakeholders to advance our understanding of how Netflix content is promoted to our members. Note that you will be jumping in at an exciting time for personalization systems - this role will help us redefine what a Netflix subscription means for our members around the world!

In this role, you will:

• Ensure that our personalization systems produce trustworthy, high-quality outputs to maximize our members' experience.

• Develop a robust framework, combining online and offline methods, to comprehensively understand the outputs of our recommendations.

• Research and incubate evaluation methods in the product by partnering early and often with our Algorithm Engineering teams.

• Establish strong partnerships with stakeholders to shape the vision of a space, whether that is by helping determine a product strategy or define new metrics.

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 focused on building and delivering real-world machine learning models with demonstrated impact.

• Strong interest and experience with LLMs.

• Strong Quantitative Programming skills in a language such as Python.

• Exceptional oral and written communication skills.

• Passion for driving product vision and innovation strategy by leveraging a broad set of techniques and building strong partnerships with stakeholders.

• Ability to work independently and drive your own projects.

• Embodies Netflix values (https://jobs.netflix.com/culture) while bringing a new perspective to continue to improve 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 (https://jobs.netflix.com/work-life-philosophy) .

  Netflix is a unique culture and environment. Learn more here (https://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, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

  Job is open for no less than 7 days and will be removed when the position is filled.