Research Scientist 5 - Ads, Identity Matching

Posted Yesterday
Be an Early Applicant
Hiring Remotely in USA
Remote
466K-750K Annually
Senior level
News + Entertainment
The Role
Conduct research and develop identity and probabilistic-matching models for Netflix's ad-supported tier. Apply ML and statistical methods, ensure privacy-preserving solutions (differential privacy, anonymization), prototype and deploy production models, deliver datasets and tools, and partner with product, engineering, and business stakeholders to measure and drive impact.
Summary Generated by Built In

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 new business area for Netflix!
 

Our goal in the Ided 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 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 Research Scientist to focus on identity modeling for our ads audience, including identity modeling, probabilistic matching, differential privacy, and anonymization.

Responsibilities 
  • ​​Apply modeling and machine learning techniques to business problems at the intersection of product and data science

  • Autonomously identify and pursue research with significant business impact, and make compelling cases for prioritization and resource allocation

  • Diagnose data and model assumptions, curating and testing appropriate models for each dataset and business objective

  • Identify, compute and validate the appropriate metrics to measure success

  • Deliver well-documented datasets, tools, and reports to key technical and business partners

  • Serve as a strategic thought partner to product managers and business stakeholders, directly influencing product direction and improving user experience. 

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

  • Effectively communicate findings and insights to both technical and non-technical audiences, driving adoption and understanding of ML-driven solutions.

Qualifications 
  • Advanced degree (PhD or Master’s) in Computer Science, Statistics, Economics, Applied Mathematics, or related quantitative field

  • 5+ years of experience and high proficiency in SQL, Python

  • 5+ years of experience with large scale data

  • Deep knowledge of machine learning, statistical modeling, and data analysis techniques

  • Experience with prototyping and deploying models using large-scale production data

  • Strong business acumen and ability to translate technical results into business impact

  • Excellent communication and collaboration skills

  • Experience in privacy, differential privacy, anonymization and identity-related concepts


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 $466,000.00 - $750,000.00. 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.

Skills Required

  • Advanced degree (PhD or Master's) in Computer Science, Statistics, Economics, Applied Mathematics, or related quantitative field
  • 5+ years of experience and high proficiency in SQL and Python
  • 5+ years of experience working with large-scale data
  • Deep knowledge of machine learning, statistical modeling, and data analysis techniques
  • Experience prototyping and deploying models using large-scale production data
  • Experience in privacy, differential privacy, anonymization and identity-related concepts
  • Strong business acumen and ability to translate technical results into business impact
  • Excellent communication and collaboration skills

Netflix Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.

  • Fair & Transparent Compensation Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
  • Equity Value & Accessibility Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
  • Healthcare Strength Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.

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The Company
HQ: Los Gatos, CA
13,212 Employees
Year Founded: 1997

What We Do

Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

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