Senior Applied Scientist, Advertiser Demand Intelligence

Microsoft•Redmond, WA

23h•$119,800 - $261,000•Hybrid

About The Position

The Demand Intelligence team is building AI-powered intelligence systems that transform large-scale marketplace and advertiser signals into actionable insights, recommendations, forecasts, and automated decision support for Microsoft Advertising. By combining advanced machine learning, generative AI, and agentic technologies that continuously analyze demand, market dynamics, advertiser behavior, campaign performance, and ecosystem trends we help stakeholders identify opportunities, optimize outcomes, understand market dynamics, and make better business decisions at scale. As a Senior Applied Scientist, you will lead the development of state-of-the-art AI solutions spanning recommendation systems, forecasting, anomaly detection, insight generation, and agentic reasoning. You will leverage LLMs, predictive modeling, retrieval systems, and modern machine learning techniques to build intelligent products that move users beyond data exploration toward automated intelligence and action. Working closely with cross-functional partners, you will drive innovations that shape the future of AI-driven decision intelligence across Microsoft Advertising. 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 4+ years related experience (e.g., statistics predictive analytics, research)
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)
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)
equivalent experience.
3+ years of hands-on experience developing machine learning or statistical models to solve real-world problems (in industry or academic projects), including building and validating algorithms such as regressions, classifiers, or clustering models.
Proven programming and data skills, including proficiency in Python and SQL, with experience working with large-scale structured and unstructured datasets.
Proven analytical and problem-solving skills, with the ability to work with messy data, identify trends or anomalies, and rigorously evaluate model performance.
Effective communication skills for presenting complex analysis in a clear manner and working collaboratively on a multidisciplinary team.
Experience building machine learning systems that generate actionable recommendations, or optimization guidance from large-scale business or marketplace signals.
Advanced Analytics: Expertise in predictive modeling, time-series forecasting, anomaly detection, or business diagnostics that drive measurable customer or business outcomes.
Generative AI & Agentic Systems: Experience applying LLMs, retrieval-augmented generation (RAG), AI agents, or reasoning systems to automate analysis, generate insights, explain recommendations, or support complex decision-making workflows.
Large-Scale Intelligence Platforms: Experience developing and deploying machine learning solutions on cloud-scale data platforms, including distributed data processing, model orchestration, experimentation, and production AI systems.

Nice To Haves

Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
equivalent experience.

Responsibilities

Lead the AI and machine learning strategy for Demand Intelligence, building solutions that transform complex marketplace and advertiser signals into actionable recommendations, insights, and decision support.
Drive innovation in predictive intelligence, including forecasting, opportunity discovery, anomaly detection, and automated insight generation that help customers achieve better business outcomes.
Build and advance Generative AI and agentic experiences that help stakeholders move from data to action more effectively.
Partner across engineering, product, and business teams to translate customer needs into scalable AI-powered products and ensure successful delivery of high-impact solutions.
Raise the technical bar by providing scientific leadership, mentoring engineers and scientists, and championing best practices in experimentation, machine learning, and responsible AI.
Establish rigorous evaluation frameworks to ensure recommendations and insights are accurate, trustworthy, measurable, and aligned with customer and business goals.
Shape the future of Demand Intelligence by identifying emerging AI technologies and turning cutting-edge research into differentiated capabilities that drive competitive advantage.