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Netflix

Data Scientist (L5) - Ads Experimentation

Posted Yesterday
Remote
Hiring Remotely in USA
170K-720K
Senior level
Remote
Hiring Remotely in USA
170K-720K
Senior level
The role involves designing and analyzing ad experiments, collaborating with cross-functional teams, and driving product changes using advanced statistical methods and data science.
The summary above was generated by AI

Netflix is one of the world's leading entertainment services, with over 300 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.

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 Senior 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 contributor driving this area for Netflix.

You will help drive innovations by effectively identifying and applying analytics, causal inference, and experimentation. This is a high-impact role in which you will have a direct influence on how product decisions are made.

In this role, you will:

  • Work with stakeholders to design, configure, run and analyze experiments related to Ads.  

  • Identify opportunities related to Ads Experimentation, 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.

  • Execute and present strong research and insights, disseminate knowledge and get others behind their ideas, and foster an open environment of collaboration, innovation, and intellectual excitement.

  • Deliver technically excellent solutions 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.

  • Experience with large-scale data with proven ability to lead cross-functionally, work independently and galvanize others .

  • Strong statistical knowledge and intuition - having 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

  • Exemplary stewardship of Netflix’s culture and values, 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 $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.

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.

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

Top Skills

Python
R
SQL

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