Principal Applied Scientist – Sales Insights Platform

Redmond, Washington, United States

• 1 more location

Date posted

Oct 29, 2025

Job number

1903543

Work site

4 days / week in-office

Travel

0-25%

Role type

Individual Contributor

Profession

Research, Applied, & Data Sciences

Discipline

Applied Sciences

Employment type

Full-Time

We are building a scalable, Azure-based analytics platform that delivers rich, customer-level sales insights and proactive alerts to Microsoft's internal sales and account management teams. This platform provides a comprehensive view of each enterprise customer by surfacing insights like abnormal revenue changes, share-of-wallet opportunities, peer benchmarks, competitive keyword gaps, and product feature adoption health, on a daily and real-time basis.

The underlying system leverages traditional machine learning models for data-driven analysis and augments the delivery of insights with agentic inter‑operation using large language models (LLMs) to generate meeting briefs, pitch assets, follow‑ups, and safe CRM updates for our sales agents.

As a Principal Applied Scientist, you will define technical vision and lead the development of both the ML and LLM components of this platform, ensuring it scales across millions of data points and delivers trusted, actionable intelligence that drives business decisions.

This role is available in either Redmond, WA or Mountain View, CA.

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.

Required Qualifications:

• Bachelor's Degree in Computer Science, Statistics, Electrical/Computer Engineering, or related field AND 6+ years of related experience (e.g. machine learning, data science, AI product development);
• OR Master's Degree in a related field AND 4+ years of related experience;
• OR PhD in a related field AND 3+ years of related experience;
• OR equivalent experience.
• 5+ years of experience with developing and deploying machine learning solutions in production, with proven ownership of complex projects end-to-end (from problem formulation and data acquisition to model deployment and monitoring).
• 3+ years of technical leadership experience in an applied science or data science team setting – this could include leading a team of scientists or acting as the key technical decision-maker on cross-discipline projects, with responsibility for delivering major features or systems.
• 3+ years of Extensive hands-on expertise in ML techniques for predictive analytics, pattern recognition, and optimization. You should be comfortable selecting and tuning algorithms for regression, classification, clustering, time-series forecasting, etc., and understand their trade-offs.

Preferred Qualifications:

• 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.
• 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• 5+ years experience conducting research as part of a research program (in academic or industry settings).
• 3+ years experience developing and deploying live production systems, as part of a product team.
• 3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
• Extensive hands-on expertise in ML techniques for predictive analytics, pattern recognition, and optimization. You should be comfortable selecting and tuning algorithms for regression, classification, clustering, time-series forecasting, etc., and understand their trade-offs.
• Programming & Data Infrastructure: Proven coding skills in ML-focused languages (e.g., Python), experience with frameworks like PyTorch/TensorFlow, and familiarity with data pipelines and databases.
• LLMs & Domain Applications: Deep understanding of NLP and large language models, with hands-on experience in applying LLMs to domain-heavy contexts (e.g., healthcare, agriculture, social sciences) while ensuring privacy and Responsible AI compliance.
• Cloud & MLOps Expertise: Proven ability to build scalable ML pipelines on cloud platforms (Azure, etc.), implement automated training, monitoring, and governance for secure and compliant AI systems.
• Leadership & Impact: Track record of driving cross-organizational alignment, delivering innovative AI solutions, and contributing to research, patents, or community leadership.

Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

• Define and drive the modeling strategy for the Sales Insights platform, spanning classical machine learning (for analytics on structured data) and the use of generative AI (for insight summarization). You will set the direction on which problems to tackle with ML (e.g. anomaly detection, predictive modeling, clustering) and how to leverage LLMs to maximize user understanding and value.
• Architect end-to-end machine learning pipelines – oversee the design of data processing workflows, feature stores, model training/validation routines, and deployment mechanisms that can reliably produce daily insights for all customers. Ensure these pipelines are scalable, efficient, and maintainable, working closely with data engineering leaders on implementation.
• Lead the incorporation of LLM-based components for the platform's intelligent narrative generation. This includes guiding the development of prompt frameworks, fine-tuning strategies, and retrieval-augmented techniques so that the system can answer complex sales questions and explain insights in conversational language.
• Oversee cross-team initiatives and collaboration, coordinating with engineering, program management, and stakeholder teams. You will chair technical design reviews, balance priorities, and guarantee that the data science efforts align with product requirements and timelines.
• Mentor and develop the applied science team, providing technical guidance to other scientists and engineers. Champion best practices in experimentation, coding, and MLOps, and foster a culture of scientific excellence and continuous learning.
• Ensure robust evaluation and governance of all AI/ML solutions. You will establish metrics for success (accuracy, precision of alerts, coverage of insights), closely monitor model performance in production, and implement processes for periodic retraining, validation, and Responsible AI compliance (addressing bias, fairness, and transparency).
• Stay ahead of the curve by tracking emerging trends in AI, whether it's new algorithms in anomaly detection or breakthroughs in large language models, and assess their potential to enhance the platform. Drive the incubation of innovative ideas, experimentally verify their benefits, and incorporate promising approaches to keep the platform technologically ahead and highly effective.

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

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Industry leading healthcare

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Educational resources

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Discounts on products and services

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Savings and investments

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Maternity and paternity leave

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Generous time away

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Giving programs

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Opportunities to network and connect

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.