채용
Benefits & Perks
•Healthcare
•Mental Health
•401(k)
•Equity
•Flexible PTO
•Healthcare
•Mental Health
•401k
•Equity
Required Skills
Machine Learning
Statistics
Python
SQL
Identity Modeling
Differential Privacy
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.
In April 2022, we announced that we are creating a new lower-priced, ad-supported tier for our customers. We are now working toward our goal of providing more choice for consumers and a premium, better-than-linear TV brand experience for advertisers. We are now hiring for the founding data scientists in this fast evolving business area for Netflix!
Our goal in the Ads Audience & Identity Science team is to deepen our understanding of our ad-tier members, in order to improve advertiser performance and ensure a great member experience. We continually improve ad targeting capabilities through identity modeling, machine learning, analytics, data exploration, and optimization. Our work includes feature engineering, modeling, lookalike algorithms, and optimization. We also provide modeling and analytics support for Netflix live content and integrations with third-party partners, with a high priority on privacy and data security. We focus on repeatable, scalable modeling for a variety of current and future applications.
This role is for a Data Scientist (L5) to focus identity modeling for our ads member base, including identity modeling, probabilistic matching, graph analytics, differential privacy, anonymization, and identity metrics.
Responsibilities
-
Apply modeling and machine learning techniques to business problems at the intersection of product and data science
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Autonomously identify and pursue research with significant business impact, and make compelling cases for prioritization and resource allocation
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Diagnose data and model assumptions, curating and testing appropriate models for each dataset and business objective
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Identify, compute and validate the appropriate metrics to measure success
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Deliver well-documented datasets, tools, and reports to key technical and business partners
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Serve as a strategic thought partner to product managers and business stakeholders, directly influencing product direction and improving user experience.
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Cultivate strong partnerships with cross-functional stakeholders from product, engineering, operations, design, consumer research, etc.
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Effectively communicate findings and insights to both technical and non-technical audiences, driving adoption and understanding of ML-driven solutions.
Qualifications
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Advanced degree (PhD or Master’s) in Computer Science, Statistics, Economics, Applied Mathematics, or related quantitative field
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5+ years of experience and high proficiency in SQL, Python; 5+ years of experience with large scale data
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Deep knowledge of machine learning, statistics, optimization, and data analysis techniques
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Experience in identity graphs, privacy, differential privacy, anonymization and identity-related concepts
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Strong business acumen and ability to translate technical results into business impact
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Excellent communication and collaboration skills
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Comfortable with ambiguity; able to thrive with minimal oversight and process
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Prior experience in ad tech, streaming, technology, or consumer-facing products is a plus.
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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About Netflix

Netflix
PublicAn online streaming platform that enables users to watch TV shows and movies.
10,001+
Employees
Los Gatos
Headquarters
$280B
Valuation
Reviews
4.2
15 reviews
Work Life Balance
4.2
Compensation
4.5
Culture
3.2
Career
3.8
Management
3.0
65%
Recommend to a Friend
Pros
Very high compensation packages (430k-700k)
Fully remote work opportunities
All cash compensation structure
Cons
Lower compensation than expected in some cases
Difficult interview process
Simple/uninteresting technical problems
Salary Ranges
1,869 data points
L3
L4
L5
L6
Mid/L4
Senior/L5
L3 · Data Scientist
0 reports
$242,500
total / year
Base
-
Stock
-
Bonus
-
$206,125
$278,875
Interview Experience
4 interviews
Difficulty
4.0
/ 5
Offer Rate
25%
Experience
Positive 25%
Neutral 25%
Negative 50%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
System Design Interview
5
Behavioral Interview
6
Team Matching
7
Final Round
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
News & Buzz
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