Principal Applied Scientist

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.

Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

• 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.

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
• 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• 5+ years experience conducting research as part of a research program (in academic or industry settings).
• 3+ years experience developing and deploying live production systems, as part of a product team.
• 3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.