Applied Scientist II
Microsoft
Applied Scientist II
Redmond, Washington, United States
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Overview
Microsoft is innovating rapidly in the advertising space to grow its share of this market by providing the ad industry with the state-of-the-art online advertising platform and service and Microsoft's advertising team is at the core of this effort.
We are hiring for multiple Applied Scientist II roles on Microsoft Advertising for the following teams
Signals Modeling Team:
Our team focuses on understanding and predicting how the user interacts with the ads on the search results page. The probability that a user will click on an ad is one of the most critical inputs used in ranking the ads. Similarly, the probability of interacting with the advertiser’s page is important for measuring advertiser and user satisfaction.
This team builds machine learning models for predicting such events. The team looks at all aspects of modeling including training data, features, the actual model (neural nets, linear models, decision trees etc.) and offline and online evaluation of those models.
Engineers and scientists on our team work at the edge of machine learning and economics developing in the online stack as well as offline workflows. At its core, our team utilizes signals of user and advertiser intent to determine which ads are allocated and at what price.
Demand Intelligence Team:
This team works on the demand optimization initiatives working on various problems including recommendation algorithms and platform components, agentic workflows for advertisers, forecasting solutions for insights and various other initiatives.
You will:
- play a key role in driving algorithmic improvements to online and offline systems, developing, and delivering robust and scalable solutions, making direct impacts on both users and advertisers experience, and continually increasing the revenue for Microsoft Ads.
- Work on the demand optimization initiatives working on various problems including recommendation algorithms and platform components, agentic workflows for advertisers, forecasting solutions for insights and various other initiatives.
- play a key role in driving algorithmic improvements to online and offline systems, developing, and delivering robust and scalable solutions, making direct impacts on both users and advertisers experience, and continually increasing the revenue for Microsoft Ads. They will heavily use the recent advances in GenAI to harness huge volume of data for solving many of the above-mentioned problems and leverage the evolving technologies.
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.
Qualifications
Required Qualifications:
- 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.
- 2+ years of experience in machine learning, deep learning, NLP, and statistics.
- 1+ years’ experience in software development.
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.
- Research experience (publications) in the following areas: statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference.
- Proven experience in programming and data analysis skills.
- Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, or transformers.
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
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
#MicrosoftAI
Responsibilities
As Applied Scientist II on Signals Modeling Team you will be responsible to:
- Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.
- Design scalable algorithms for online and offline systems, delivering innovative solutions for content selection, user engagement modeling, and ad generation.
- Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.
- Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.
- Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.
As Applied Scientist II on Demand Intelligence team you will be responsible for:
- Developing Recommendation algorithms in Bid/Budgets/Keywords etc.
- Selection and Ranking components for Campaign recommendation platform.
- Agentic workflows for campaign optimization.
- Forecasting solutions
- Demand analytical tools
- Experimentation infrastructure, dashboard, live marketplace monitoring, and diagnosis