Research Scientist 5 - Ads, Identity Matching

Netflix•,

3d•$466,000 - $750,000

About The Position

In April 2022, Netflix announced the creation of a new lower-priced, ad-supported tier. The company is now working towards providing more choice for consumers and a premium, better-than-linear TV brand experience for advertisers. This role is for a founding data scientist in this new business area for Netflix, focusing on identity modeling for the ads audience, including identity modeling, probabilistic matching, differential privacy, and anonymization. The goal of the Identity Science team is to deepen the understanding of ad-tier members to improve advertiser performance and ensure a great member experience. This is achieved through continuous improvement of ad targeting capabilities using machine learning, analytics, data exploration, and optimization. Work includes feature engineering, modeling, lookalike algorithms, and optimization. The team also provides modeling and analytics support for Netflix live content and integrations with third-party partners, with a high priority on privacy and data security. The focus is on repeatable, scalable modeling for a variety of current and future applications.

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.