Principal Applied Science Manager - Excel Team

Microsoft•Redmond, WA

15h•$142,800 - $304,200

About The Position

This Principal Applied Science Manager role on the Microsoft Excel team is an opportunity to lead a fast-paced, high-visibility, diverse team delivering innovative AI capabilities across flagship Microsoft products. The role involves leading and developing a team of applied scientists responsible for architecting, designing, and delivering AI-powered experiences that help customers work more effectively in Microsoft Excel. The team will apply state-of-the-art techniques in large language models, deep learning, information retrieval, agent orchestration, and evaluation. The role includes setting the end-to-end scientific direction for Excel’s agentic AI and evaluation systems, translating customer needs, real-world usage patterns, and product failure modes into clear research, engineering, and product priorities. The role will also expand to science work building key scenarios, such as finance, across the whole suite of Microsoft's tools. This is a deeply technical leadership role for a hands-on builder who can balance people management, technical strategy, and individual contribution, partnering closely with engineering, product management, customers, and Microsoft’s broader AI, research, and platform communities. The ideal candidate is passionate about maintaining a high scientific bar, building inclusive and high-performing teams, and delivering reliable, customer-impacting AI capabilities.

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.
1+ year(s) of people management experience.
Ability to meet Microsoft, customer and/or government security screening requirements.
Ability to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

4+ years of experience applying machine learning techniques and driving end-to-end AI product development from concept to shipping
3+ years of experience working with large language models.
3+ years of experience as a manager of a successful and impactful data science/applied science team with 5 or more direct reports.
Demonstrated experience leading complex technical projects from problem definition and experimentation through production deployment and iteration.
Experience mentoring, leading, or managing applied scientists, data scientists, machine learning engineers, or other technical contributors.
Ability to work effectively across engineering, product management, design, and research partners in a fast-paced and ambiguous environment.
Ability to explain technical tradeoffs, evaluation results, and product implications to a broad set of stakeholders.
Demonstrated ability to lead end-to-end work in challenging technical domains, including planning, design, execution, continuous release, and service operation.
Experience shipping internet-scale, low-latency, highly available intelligent systems.
Experience with Microsoft Excel or building AI experiences for productivity applications is a plus.
Experience applying foundation models, including domain adaptation, fine-tuning, and evaluation of LLMs or small language models.
Experience with prompt optimization, retrieval-augmented generation, data mining using language models, and agentic systems.
Experience with AI evaluation, including benchmark design, human evaluation, model-quality analysis, safety assessment, and telemetry-driven iteration.

Responsibilities

Lead, grow, mentor, and inspire an inclusive, high-performing team of applied scientists. Support individual career development and guide team members through complex technical and product problem spaces.
Maintain a hands-on, builder-oriented approach, contributing directly to technical design, prototyping, experimentation, implementation, and production readiness as needed.
Own the end-to-end technical and scientific direction for your team’s AI capabilities, from identifying customer scenarios and defining success criteria through experimentation, evaluation, deployment, and continuous improvement.
Translate product scenarios and customer needs into well-defined machine learning, LLM, retrieval, program synthesis, and agentic-system problems; identify key technical challenges and design experiments to address them.
Drive projects from concept through implementation, experimentation, production integration, and successful release to customers.
Establish and maintain a high scientific and engineering bar for model quality, reliability, safety, latency, cost, and customer value.
Design and drive rigorous evaluation frameworks for intelligent applications, using offline metrics, human evaluation, telemetry, real-world feedback, and failure analysis to identify opportunities for improvement.
Work directly with customers and partners to understand real-world usage patterns, pain points, and failure modes, translating those insights into product, scientific, and engineering priorities.
Lead the preparation, curation, and quality assessment of datasets used for modeling, evaluation, and experimentation, including identifying data quality constraints and opportunities.
Stay current on relevant research, industry trends, and emerging techniques, applying them pragmatically to customer-facing Excel experiences.
Collaborate across the Office Product Group and the broader Microsoft AI, research, and platform communities to share evaluation practices, adopt and contribute to common infrastructure, and avoid duplicated investment.