Applied Scientist at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Mar, 26

Salary

199000.0

Posted On

21 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Statistical Analysis, Data Processing, Collaboration, Model Evaluation, Prompt Engineering, Responsible AI, Anomaly Detection, Time-Series Analysis, Business Intelligence, Sales Analytics, Marketing Analytics, Large Language Models, Forecasting, Data-Driven Insights, Scalable Models

Industry

Software Development

Description

Overview 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. 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. Qualifications Required: 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. Preferred Qualifications: 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. #MicrosoftAI Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

The Applied Scientist II will design and develop scalable ML models for advertiser recommendations and insights. They will collaborate with engineering teams to operationalize these models and integrate LLM-driven reasoning into workflows.