Senior Applied Scientist

Signals Modeling team:

(This role is available in Mountain View, CA, Redmond, WA or New York, NY.)

The 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.

The role for this team is focused on building machine learned 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.

We are building a scalable, Azure-native platform that provides up-to-date sales insights for Microsoft’s internal sales and account teams. This platform surfaces critical information such as revenue anomalies, share-of-wallet metrics, peer benchmarks, keyword gap analyses, and feature adoption health checks for our enterprise customers.

The core insights are driven by classical machine learning models (for forecasting, anomaly detection, clustering, etc.). Agentic inter operation using LLMs convert these results into concise briefs, pitch deck drafts, follow ups, alerts, CRM updates, and engagement artifacts.

As a Senior Applied Scientist, you will lead the development of these machine learning solutions and the integration of LLM-based summarization, ensuring the platform delivers accurate, actionable intelligence at scale.

Demand Intelligence Team:

(This role is available in Redmond, WA.)

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.

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.

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.

Required Qualifications:

Preferred Qualifications:

• Proven experience in programming and data analysis skills.
• Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, or transformers.
  

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

#MicrosoftAI #MAI, #MSAN, #Copilot #GTA

As a Senior Applied Scientist 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 a Senior Applied Scientist on Sales Intelligence for Microsoft Ads team you will be responsible to:

• Lead the design and implementation of machine learning models for anomaly detection, forecasting, and customer segmentation.
• Drive experimentation and validation of models.
• Mentor other early in profession scientists and contribute to model governance and Responsible AI practices.
• Partner with engineering and BI teams to operationalize insights into dashboards and alerting systems.
• Advance feature adoption scoring and health check analytics through data-driven approaches.
• Engineer optimal prompts for various LLM calls, using chain-of-thought and other advanced techniques.
• Fine-tune SLMs to efficiently scale the solution to millions of advertisers.
• Generate account planning guidance, tailored talking points, pitch assets, follow ups using agentic orchestration.

As a Senior Applied Scientist 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