# Principal Applied Scientist

**Company**: Microsoft
**Location**: Redmond
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $139,900 – $274,800 per year
**Category**: Engineering
**Industry**: Technology
**Ticker**: MSFT
**Wikidata**: https://www.wikidata.org/wiki/Q2283

**Apply**: https://microsoft.ai/job/principal-applied-scientist-10/
**Canonical**: https://yubhub.co/jobs/job_b2f91c0a-0b3

## Description

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.

Responsibilities:

* 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.

Technical & Engineering Execution:

* 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.

Business & Product Impact:

* 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.

Leadership & Mentorship:

* 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.

Innovation & Tooling:

* 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.

Qualifications:

* 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 (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

## Skills

### Required
- Machine Learning
- Deep Learning
- Statistics
- Econometrics
- Computer Science
- Electrical or Computer Engineering

### Nice to have
- LLM-based tooling
- Experiment design
- Ablations
- Feature validation
- Productionization