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Netflix
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Data Scientist (L5) - Promotional Media Measurement Science
United States
· Full-time
·
Not Applicable
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.
The Promotional Media Measurement Science team (part of Netflix’s Data Science and Engineering organization) conducts deep research on and develops metrics about the relationship between promotional media and member engagement, to ultimately influence the creation and deployment of titles’ promotional assets. Our team utilizes cutting-edge methods from experimentation, causal inference, predictive modeling and machine learning for concrete applications and to contribute to methodological innovation both internally at Netflix and externally at leading tech and academic conferences. We collaborate closely with our partners in product, engineering, marketing in order to shape algorithmic, strategic and creative decisions related to promotional media at Netflix.
We are looking for a talented senior data scientist to drive technical innovation and produce bottom-line impact on Netflix’s business by developing models, metrics and insights to improve the creation and optimization of promotional assets. Interested? Read more about the job description and qualifications below!
What You Will Do
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.
The Promotional Media Measurement Science team (part of Netflix’s Data Science and Engineering organization) conducts deep research on and develops metrics about the relationship between promotional media and member engagement, to ultimately influence the creation and deployment of titles’ promotional assets. Our team utilizes cutting-edge methods from experimentation, causal inference, predictive modeling and machine learning for concrete applications and to contribute to methodological innovation both internally at Netflix and externally at leading tech and academic conferences. We collaborate closely with our partners in product, engineering, marketing in order to shape algorithmic, strategic and creative decisions related to promotional media at Netflix.
We are looking for a talented senior data scientist to drive technical innovation and produce bottom-line impact on Netflix’s business by developing models, metrics and insights to improve the creation and optimization of promotional assets. Interested? Read more about the job description and qualifications below!
What You Will Do
- Build models to predict the performance of promotional assets, estimate the contribution of those assets to content performance, and quantify the revenue impact from driving member engagement
- Execute and analyze experiments and/or develop causal inference and machine learning models to identify key drivers of positive member outcomes that can be attributed to promotional assets
- Develop innovative statistical, mathematical, and machine learning methodologies to solve novel problems that Netflix faces, and share your work both internally and externally
- Partner with a diverse range of cross-functional business partners to uncover new opportunities and develop metrics and models to guide partners on asset creation and deployment
- Be a technical leader and mentor for other data scientists, analytics engineers and research scientists
- Ph.D. degree (preferred) in a quantitative or computational field such as statistics, computer science, mathematics, economics, finance, engineering, physics, etc.
- 3+ years work experience in relevant data science roles
- Expertise in statistical methods, notably regression analysis, forecasting, causal inference, and experimentation
- Knowledge of and experience in applying supervised and unsupervised machine learning methods
- Experience with time-series forecasting and/or financial modeling a plus
- Highly proficient programming in SQL and Python / R
- Comfortable and effective in ambiguous problem spaces; ability to own and drive projects with minimal oversight and process
- Exceptional written and oral communication with technical and non-technical audiences
- Enthusiasm about and compatibility with Netflix culture
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.
Key Skills
Ranked by relevance
machine learning
python
sql
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- Posted
- Oct 03, 2025
- Type
- Full-time
- Level
- Not Applicable
- Location
- United States
- Company
- Netflix
Industries
Entertainment Providers
Categories
Other
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3 roles aligned with this opportunity
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