This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a Principal Applied Scientist to lead the next generation of click-through-rate (CTR) for Microsoft Advertising. This is a high-impact role responsible for advancing large-scale ranking models that power Microsoft Advertising, generating billions of impressions and revenue-critical decisions daily. You will combine deep machine learning expertise, solid engineering execution, and business intuition to modernize our prediction stack, drive model innovation, and mentor a growing team of scientists and engineers. This role is ideal for someone who thrives in complex, high-scale systems, who brings thought leadership to ML strategy, and who raises the bar for engineering rigor, curiosity, and business-driven decision making across the team.
Job Responsibility:
Lead the end-to-end development of large-scale CTR and other user response signal models for Search and Display ads
Design, prototype, and ship cutting-edge ML architectures (deep models, multi-task, transformer-based, LLM-assisted, multimodal)
Define long-term modeling strategy and roadmap with clear business impact
Modernize our current modeling pipelines, addressing critical technical debt in data flows, training pipelines, and inference systems
Partner closely with engineering teams to improve reliability, monitoring, and performance of distributed training and online serving
Introduce best practices for experiment design, ablations, feature validation, and productionization
Work with PMs, monetization teams, and auction experts to translate business needs into modeling goals
Own model performance holistically: quality, stability, latency, and revenue impact
Develop frameworks to better understand advertiser value, user behavior, and marketplace dynamics
Mentor and up-level applied scientists and ML engineers across the organization
Drive a culture of curiosity, deep system understanding, and high-quality scientific reasoning
Improve collaboration norms, documentation quality, and cross-team alignment
Leverage and influence LLM-based tooling (e.g., agents, copilots) to improve team productivity and model development velocity
Identify opportunities to incorporate new modeling signals, architectures, or evaluation metrics
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience