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Microsoft Corporation Logo Microsoft Corporation · IT - Software Development

Principal Applied Science Manager - Excel Core

United States, Redmond 139900.00 - 274800.00 USD / Year · Job Posted March 04, 2026
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Job Description

Excel is one of the most widely used and impactful software programs in the world, powering solutions for businesses and individuals across every industry. We are seeking a Principal Applied Science Manager to join the Excel Core team—an opportunity to shape the future of productivity and influence hundreds of millions of users globally. Your mission: bring cutting-edge Artificial Intelligence (AI) technologies, patterns, and model capabilities into production, delivering intelligent experiences directly in the Excel grid. As a Principal Applied Science Manager, you will work at the intersection of research and engineering—leading an Applied Science team, writing production-quality code, collaborating with researchers and engineers, and fostering a culture of rapid experimentation that ships. You’ll help define the next generation of AI-powered features in Excel, blending scientific rigor with engineering excellence to create experiences that delight users and transform workflows.

Job Responsibility

  • Defining, leading, and helping to conduct research projects that simultaneously advance the state-of-the-art and directly benefit Microsoft’s core productivity products
  • Drive complex orchestration of Copilot workflows and agent pipelines, blending prompt engineering, tool invocation, and context grounding for productivity scenarios
  • Contribute to the end-to-end development, deployment, and continuous improvement of advanced multimodal machine learning (ML)/ large language model (LLM) systems—including dataset curation, labeling strategy, model architecture, scalable training, and rigorous evaluation (offline and online)
  • Stay current with research and industry trends, identifying opportunities to integrate emerging technologies and methods into the Excel Core ecosystem across the entire spectrum of AI adoption
  • Effectively communicating with product leaders (and often Microsoft researchers (MSR)) throughout the planning and execution of applied research projects, which often involves learning and teaching complex concepts
  • Collaborate with engineering and product teams to define success metrics, design and execute experiments (e.g., A/B testing), monitor user signals, and iterate on deployed features
  • Embody our culture and values

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
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • OR equivalent experience
  • 1+ year(s) of people management experience
  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter

Nice to have

  • Experience orchestrating LLM-based agent pipelines - prompt engineering, tool invocation, context grounding and evaluation - for productivity scenarios, alongside other advanced ML techniques
  • Advanced degree (Master or PhD) in Computer Science, Math, Statistics, or related areas with industry experience or research publication in LLMs, ML, or Natural language processing (NLP)
  • Proven expertise and background in designing and implementing AI models that serve millions of users in scaled production environments or agent-based workflows for real-world productivity applications
  • Demonstrated success moving applied research into shipped product features, with clear ownership of the end-to-end ML lifecycle—data collection, cleaning, modeling, evaluation, prompt engineering and continuous improvement
  • Experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • Deep understanding of transformer-based architectures and hands-on experience with model optimization techniques (quantization, pruning, distillation, adapter tuning)
  • Customer-obsessed mentality and passion for translating research breakthroughs into meaningful product impact
  • Experience in designing and debugging complex services
  • Ability to communicate and collaborate with multiple teams
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