Applied Scientist

Microsoft • Redmond, WA

6d • $100,600 - $199,000 • Hybrid

About The Position

We are building a large-scale, Azure-based intelligence platform that turns complex data into high-quality, actionable insights for Microsoft Advertising. This platform combines advanced machine learning with emerging agentic capabilities powered by large language models (LLMs) to deliver smarter recommendations, automate analysis, generate contextual summaries, and streamline workflows across the ecosystem. We are looking for an Applied Scientist II to help advance this platform. In this role, you will design and develop scalable ML models, partner closely with engineering teams to productionize solutions, and integrate LLM-driven reasoning and summarization into core workflows. This is an opportunity to work on cutting-edge applied science challenges that directly influence advertiser experience and platform performance. 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.

Requirements

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• OR equivalent experience.

Nice To Haves

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• Hands-on experience developing and validating ML/statistical models (e.g., regressions, classifiers, clustering).
• Experience with large-scale data processing or distributed computing (e.g., Spark, Azure Databricks).
• Familiarity with time-series analysis and anomaly detection techniques (e.g., ARIMA, isolation forests).
• Exposure to LLMs and prompt engineering for summarization or domain adaptation.
• Domain knowledge in sales, marketing analytics, or business intelligence.

Responsibilities

• Implement large scale ML models for advertiser recommendations, insights, and forecasting.
• Apply statistical and machine learning techniques to detect patterns, surface anomalies, and generate data-driven insights.
• Collaborate with engineering and BI teams to operationalize models into dashboards and alerting systems.
• Support experimentation and contribute to model performance evaluation.
• Assist in prompt engineering for LLM calls and explore summarization techniques.
• Ensure Responsible AI practices and contribute to model governance.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees