About the job
The Ad Ranking team within the Ads Data Science and Engineering organization is the central intelligence driving ad personalization at Netflix. The team is responsible for enhancing ad quality and performance through advanced machine learning and optimization algorithms, utilizing both proprietary and external data signals. Key areas of focus include Identity Science, User Understanding, Audience & Targeting, Relevance & Engagement Prediction, and Bidding & Pacing.
Responsibilities
Design and implement machine learning and optimization algorithms to improve ad quality and performance.
Build, train, and evaluate models on large-scale production data.
Develop online and offline evaluation frameworks to rigorously measure the impact of model and algorithm improvements.
Partner closely with the product team to define optimization objectives, constraints, and trade-offs that align with product and business goals.
Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders, driving understanding and adoption of ML-driven solutions.
Qualifications
Minimum
Advanced degree (PhD or Master’s) in Computer Science, Statistics, Mathematics, or related quantitative field.
Proficiency in Python, Scala or Java.
Deep knowledge of machine learning, optimization, and data analysis techniques.
Experience with prototyping and deploying algorithms using large-scale production data.
Strong business acumen and ability to translate technical results into business impact.
Experience in ad optimization stack, e.g. targeting, ranking, bidding..
Excellent communication and collaboration skills.
Preferred
No preferred qualifications listed.