Data Scientist (L5) - Ads (Experimentation)

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.

At Netflix, we seek to entertain the world. We have more than 200 million members in 190 countries, reflecting that great stories can come from anywhere and be loved everywhere. 

In Nov 2022, we launched a new lower-priced, ad-supported tier for our customers. We are now continuing to build on our goal of providing more choice for consumers and a premium, better-than-linear TV brand experience for advertisers. That said, we are looking for the founding members of this new business area for Netflix! 

The Ads Data Science and Engineering team at Netflix’s mission is to help build the foundation of the ads business at Netflix. We conduct analyses and develop analytic tools, build predictive models and algorithms using machine learning, all with the goal of creating more choices and joy for our members. You’ll work closely with partner teams to build workflows, provide recommendations and drive success on end-to-end analytics initiatives in this 0 -1 space.

We are seeking a Data Scientist who can help with foundational problems like Experimentation and Valuation in the ads space. This is an opportunity to partner with a diverse range of cross-functional business partners to uncover new opportunities, design, execute, and analyze experiments, and deliver solutions that have a significant business impact and implications for our users. Experimentation techniques are crucial to the long-term success of our ads business, and you will be a key thought partner in this area for Netflix.

You will help drive innovations through effective identification and application of analytics, causal inference, experimentation and machine learning. This is a high-impact role in which you will have direct influence on how product decisions are made. 

In this role, you will:

• Enable scalable and trustworthy experimentation for our newer Ads business.  Initially this role will include defining evaluation metrics, determining the proper design and setup for experiments and conducting manual/adhoc analyses.  And will evolve into leveraging our existing Netflix Experimentation Platform, defining and educating on Ads Experimentation best practices and enabling informed decision making at scale.

• Be a thought partner in the area of Experimentation for Ads Platform, and autonomously identify and pursue research with significant business impact, and make compelling cases for prioritization and resource allocation.

• Cultivate strong partnerships with cross-functional stakeholders from product, engineering, operations, design, consumer research, etc.

• Deliver technically excellent solutions using modeling and ML, data exploration and strong documentation with an eye toward impact and contribution to the larger DSE community.

• Be a thought leader for Product, Strategy and Engineering teams in the areas of Experimentation for Ads.

We are looking for:

• Advanced degree in Statistics, Mathematics, Physics, Economics or related quantitative field.

• Strong statistical knowledge and intuition - having been utilized in experimentation or other product analytics settings.

• Strong product knowledge and intuition - having utilized in consumer/user interface settings or internally serving technical audiences such as engineers.

• Demonstrated ability to communicate and drive product change across a variety of stakeholders. 

• Strong SQL skills and Quantitative Programming skills in Python or R

• Ability to communicate technical and statistical concepts clearly and concisely among audiences at many different levels. 

• Mentors, brainstorms with, and enables others, especially within your functional area

• Actively builds and fosters technical communities internally (e.g., horizontal forums, seminars, and summits) and externally (e.g., conference participation). 

Exemplary stewardship of , particularly in terms of selflessness and ensuring open debate of ideas and encouraging inclusion of a variety of perspectives regardless of seniority.

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 $100,000 - $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.

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.

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