Applied Scientist

Microsoft • Redmond, WA

22h • Hybrid

About The Position

The Ads Monetization Algo team at Microsoft Advertising focuses on optimizing ad performance for all advertisers in our ecosystem by bidding on their behalf in real-time auctions across our marketplaces. We are also responsible for designing and optimizing the auctions for the long term. All of these works are done through algorithm development, optimization, and experimental analysis of advertiser strategies and auction mechanisms. In our team, applied scientists work together and utilize all sorts of platforms, techniques, and approaches, including but not limited to mathematical modeling and optimization, machine learning, optimal control, game theory, and general economics and operations research. We build and develop both online stacks as well as offline workflows to support our algorithms. At its core, our team utilizes signals of user and advertiser intent as well as auction characteristics to determine in real-time or near-real-time which ads can enter the auctions. Our work directly impacts 10+ billion dollars in revenue annually.
We are looking for a highly skilled applied scientist with development and management skills and a background in quantitative fields such as statistical machine learning, decision theory, operations research, optimization theory, mathematical modeling, data mining, causal inference, information retrieval, game theory, mechanism design, and optimal control. They 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 advertisers' experience and the ad marketplace's long-term health to collectively and continually increase the revenue for 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 6+ 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 4+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.

Nice To Haves

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• 8+ years of experience developing and deploying live production systems, as part of a product team.
• 3 Years of experience in Auto-Bidding or Auction Design.

Responsibilities

• Designing, implementing, and analyzing bidding strategies using techniques from optimization, control theory.
• Designing, prototyping, and analyzing different auction mechanisms given specific product area.
• Designing and overseeing large-scale, long-term experiments to improve the health of the marketplace using advanced statistics and machine learning.
• Designing automation algorithms for advertisers using techniques from AI and ML to improve advertisers’ return on investment.
• Implementing methods for optimizing the marketplace at the large scale.
• Developing models for causal reasoning using techniques from AI, ML, and statistics.

What This Job Offers

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