Senior Principal Data Scientist - Ads Measurement

It takes powerful technology to connect our brands and partners with an audience of hundreds of millions of people. Whether you're looking to write mobile app code, engineer the servers behind our massive ad tech stacks, or develop algorithms to help us process trillions of data points a day, what you do here will have a huge impact on our business-and the world., We are an industry-leading direct-to-consumer and ad tech solution for advertisers and publishers. Our innovative ad tech gives one-stop access to Yahoo, Inc.'s trusted data, high-quality inventory and demand, creative ad experiences, and industry-leading machine learning at global scale. The Consumer Monetization team's charter is to Find, Evaluate, Build, and Scale new monetization products and internal campaign tools across all Yahoo brands. We are currently transitioning our monetization engine to an AI-first framework, where autonomous agents optimize for long-term user value and advertiser outcomes in real-time., Model Training & ML Strategy

• Define the strategic technical roadmap for production-grade ML models, leveraging AI-augmented prototyping tools (e.g., SageMaker Jumpstart) to accelerate the deployment of transformer architectures and multi-task models.
• Architect multi-objective learning models that jointly optimize for publisher yield and advertiser outcomes, implementing AI-driven validation frameworks to ensure model safety and robustness.
• Establish organization-wide standards for model training pipelines, automated retraining, and AI-augmented model versioning.

Feature Generation & AI-Augmented Data Science

• Oversee the design of real-time and batch feature generation pipelines, integrating AI-driven diagnostics (e.g., Vertex AI) to monitor feature health, drift detection, and automated quality monitoring at petabyte scale.
• Implement AI-assisted tools to automate feature discovery from cross-channel signals-search intent, content engagement, and purchase behavior-to improve model predictive power.

Strategic Experimentation

• Lead the organization's experimentation strategy, utilizing AI-driven simulation environments to evaluate multi-armed bandit and causal inference designs before online deployment.
• Develop AI-powered guardrail monitoring systems that autonomously adjust experiment parameters to protect revenue while maximizing learning velocity.

Autonomous Feedback Loops

• Architect the next-generation closed-loop feedback architecture, where RL-based agents self-improve through automated reward shaping and credit assignment mechanisms.
• Lead the implementation of AI-augmented offline policy evaluation (OPE) techniques to safely validate reinforcement learning policies in highly sparse and delayed reward environments.

Leadership & Organizational Influence

• Contribute to the development of the organization's broader functional strategy, ensuring monetization science aligns with Yahoo's long-term business objectives.
• Establish governance frameworks using tools like Weights & Biases to standardize ML experiment tracking and ensure reproducibility across multiple squads.
• Mentor and provide technical guidance to senior and principal data scientists, elevating the technical bar for the entire monetization engineering organization.

• Ph.D. in Computer Science, Machine Learning, Statistics, or a related field with 8+ years of industry experience; or M.S. with 12+ years of relevant industry experience.
• Proven experience leveraging AI productivity tools and LLMs to accelerate complex research workflows and code generation.
• Proficiency in prompt engineering and structured interaction with AI models to optimize large-scale system diagnostics and research documentation.
• Deep expertise in supervised learning, gradient-boosted trees, and reinforcement learning (RL/Bandits) applied to organizational-scale problems.
• Strong proficiency in Python and SQL; experience with distributed computing (Spark) and cloud ML platforms (Vertex AI, SageMaker) for production-grade deployment.
• Expertise in exercising judgment when to deploy AI-augmented solutions versus traditional manual research approaches.

Nice to Have

• Experience in ad tech or auction design (yield management).
• Experience with AI-native research practices, including the use of agentic AI for hypothesis generation or data synthesis.
• Publications in top ML/AI venues (NeurIPS, ICML, KDD) or equivalent industry contributions.

The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies ; exercising sound judgment ; working effectively, safely and inclusively with others ; exhibiting trustworthiness and meeting expectations ; and safeguarding business operations and brand integrity.

The compensation for this position ranges from $160,965.00 - $349,885.00/yr and will vary depending on factors such as your location, skills and experience.The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more.