Principal Applied Scientist at Microsoft

Department: Applied Sciences

Compensation

$142,800 – $274,800/yr

Setup: On-site
Location: Redmond, Washington · Mountain View, California
Type: Full-time
Level: staff+
Posted: Aug 5, 2026

Description

Microsoft is hiring a Principal Applied Scientist for its Ads Fraud Detection team to lead complex fraud detection initiatives, develop scalable machine learning and low-latency production systems, and provide technical leadership across science, engineering, ads, security, and privacy teams. The role requires advanced statistical or machine learning expertise, substantial related experience, and the ability to meet Microsoft security screening requirements. Compensation is USD 142,800–274,800 per year in the United States, with higher ranges for the San Francisco Bay area and New York City metropolitan area.

Required Skills

Anomaly detection
Cross-signal analysis
Large language models
Statistical machine learning
Deep learning
Causal inference
Model operationalization
System design

Additional Information

Minimum Education: Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field
Required Previous Experiences: 6+ years of related experience in statistics, predictive analytics, or research
4+ years of related experience with a master's degree
3+ years of related experience with a doctorate
Preferred Qualifications: Master's degree and 9+ years of related experience
Doctorate and 6+ years of related experience
5+ years creating publications
2+ years presenting at conferences
5+ years conducting research
3+ years developing and deploying live production systems
3+ years developing and deploying products or systems across the product cycle
Extensive industry experience delivering production machine learning solutions
Architecting scalable machine learning systems and low-latency decision pipelines
Expertise in statistical machine learning, anomaly detection, fraud and risk modeling, deep learning, large-scale data mining, and causal inference
Setting technical direction and driving multi-year research and engineering strategy
Software engineering and system design
Mentoring and developing scientists
Communication and stakeholder management
Research impact through publications, patents, or internal innovations

About Microsoft

Microsoft

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