At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
The Ads Data Science & Engineering team is responsible for the foundational logic of the Netflix ads business. We develop the analyses, tools, and predictive algorithms that drive member joy and advertiser value. As a Data Scientist in this 0–1 space, you will not just execute tasks; you will be a primary architect of our experimentation roadmap, helping us navigate the transition from a nascent offering to a sophisticated global marketplace.
Key Responsibilities
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Scalable Experimentation & Frameworks: Design and execute rigorous experimental frameworks. You will lead the transition from manual analysis to automated, scalable solutions integrated with the Netflix Experimentation Platform, defining best practices that ensure trustworthy decision-making at scale.
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Marketplace Dynamics & Auction Theory: Drive the advancement and implementation of biddable media models and dynamically priced auctions. You will develop strategies to optimize marketplace mechanics, ensuring balance between supply, demand, and member experience.
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Global Expansion & Scaling: Partner with Product and Engineering to solve "cold-start" measurement challenges and rapidly scale our ad platform across diverse international markets.
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Strategic Thought Leadership: Act as a high-level consultant to Product, Strategy, and Engineering teams. You will autonomously identify research opportunities, quantify their potential business impact, and advocate for resource allocation to pursue them.
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Collaborative Partner: Cultivate strong partnerships with cross-functional stakeholders including product, engineering, operations, design, and consumer research.
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Technical Excellence: Deliver end-to-end solutions using advanced causal inference, machine learning, and data exploration, maintaining a high bar for documentation and reproducibility.
Requirements
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Advanced Quantitative Background: MS or PhD in a quantitative field (e.g., Statistics, Economics, Mathematics) or equivalent practical experience.
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Specialized Domain Expertise: Significant experience with auction dynamics, yield management, or supply-demand matching within a marketplace setting.
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Statistical Rigor: Mastery of causal inference and experimental design, with specific experience solving for interference and network effects in marketplace environments.
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Technical Stack: Expert proficiency in Python or R, and advanced SQL.
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Strategic Communication: Ability to translate complex statistical results into actionable business narratives for stakeholders at all levels of the organization.
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Netflix Culture: A self-starter who thrives in an environment of radical transparency and high autonomy. You are a mentor and a collaborator who prioritizes the inclusion of diverse perspectives to reach the best possible decisions.
Generally, 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 $372,000.00 - $600,000.00. This compensation range will vary based on location.
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 details 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.
Job is open for no less than 7 days and will be removed when the position is filled.
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关于Netflix

Netflix
PublicAn online streaming platform that enables users to watch TV shows and movies.
10,001+
员工数
Los Gatos
总部位置
$280B
企业估值
评价
10条评价
3.8
10条评价
工作生活平衡
2.8
薪酬
4.2
企业文化
3.9
职业发展
3.8
管理层
3.2
68%
推荐率
优点
Great benefits and compensation
Innovative and diverse culture
Supportive team and management
缺点
Fast-paced and high pressure environment
Work-life balance issues and long hours
High workload and expectations
薪资范围
1,877个数据点
L6
Mid/L4
Senior/L5
L3
L4
L5
L6 · Lead Data Scientist
0份报告
$742,500
年薪总额
基本工资
-
股票
-
奖金
-
$631,125
$853,875
面试评价
3条评价
难度
3.7
/ 5
体验
正面 0%
中性 67%
负面 33%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
System Design Interview
5
Onsite/Virtual Interviews
6
Final Round
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
最新动态
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Reddit user commented: 'Oh wow, having read that it seems like the company culture would reek of toxicity and company politics' in response to Netflix's keeper test policy.
reddit (via aggregator)
·
Netflix work life balance?
Mixed reports: some describe it as 'demanding but respectful', others call it a 'meat grinder'. WLB varies significantly by team and manager. Rating: 3.6/5 on Glassdoor.
teamblind (reddit alternative)
·
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News
·
1w ago
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The Motley Fool
News
·
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