Research Scientist 5, Signal Privacy - Ads DSE

Netflix•Los Angeles, CA

About The Position

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 Identity & Signals 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 signal privacy, including differential privacy in 3rd party signals, privacy enhanced technologies in ad targeting, ranking and optimization, and privacy related policy.

Requirements

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

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.