Role overview
Microsoft’s Online Shopping team is collaborative and interdisciplinary. You will work closely with a diverse team within Microsoft that brings together Applied Scientists, software engineers, Data engineers and Product Managers. By bringing together a unique combination of knowledge and skillsets, as well as cutting edge Technology, we build novel solutions to global online Shopping.
As a Principal Applied Scientist in the Catalog Enrichment Team, you will build production-level Machine Learning models and have them integrated in large scale data pipelines running on Billions of records with low latency. You will be responsible for solving the challenging problems that the team is facing to unblock major problems leading to improved quality and coverage of Shopping data assets and an enhanced user experience.
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.
Responsibilities
- Bringing the State of the Art to Products Independently works to create product impact. Identifies approach and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact a Microsoft product or service, and uses subject matter expertise to help others do the same. Shapes or influences the direction of Microsoft with industry-leading product/tooling work. Drives product differentiation in the market as an output of research. May publish research to promote receiving new intellectual property for product impact.
- Independently works to create product impact. Identifies approach and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact a Microsoft product or service, and uses subject matter expertise to help others do the same. Shapes or influences the direction of Microsoft with industry-leading product/tooling work. Drives product differentiation in the market as an output of research. May publish research to promote receiving new intellectual property for product impact.
- Capability Management and Networking Leverages network as well as their personal expertise and/or recognition to attract new research talent to join Microsoft. Builds trusted relationships with key internal and external stakeholders to develop long-term partnerships and advocate for research initiatives. Drives efforts to attract, screen, and interview top talent. May share research findings through publications or industry outreach as a leading expert. Collaborates with the academic community to develop the recruiting pipeline, identify cutting-edge solutions for products, and drive awareness of their work. Establishes need for new area of work.
- Leverages network as well as their personal expertise and/or recognition to attract new research talent to join Microsoft. Builds trusted relationships with key internal and external stakeholders to develop long-term partnerships and advocate for research initiatives. Drives efforts to attract, screen, and interview top talent. May share research findings through publications or industry outreach as a leading expert. Collaborates with the academic community to develop the recruiting pipeline, identify cutting-edge solutions for products, and drive awareness of their work. Establishes need for new area of work.
- Documentation Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Creates informal documentation and may share findings to promote innovation within group or with other groups. Performs higher-level extraction and distills down to core ideas. Provides leadership for team members with documentation processes used.
- Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Creates informal documentation and may share findings to promote innovation within group or with other groups. Performs higher-level extraction and distills down to core ideas. Provides leadership for team members with documentation processes used.
- Ethics and Privacy Drives discussions around ethics and privacy policies related to research processes and/or data/information collection. Integrates industry-wide ethics insights and best practices to influence internal processes and drive decision-making. Ensures that members across the discipline are aware of the potential for bias in solutions being developed.
- Drives discussions around ethics and privacy policies related to research processes and/or data/information collection. Integrates industry-wide ethics insights and best practices to influence internal processes and drive decision-making. Ensures that members across the discipline are aware of the potential for bias in solutions being developed.
- Leveraging Applied Research Champions innovative principles and forward-looking technologies related to changes in industry/market trends, advances, and opportunities in applied technologies. Develops and shares new and unique technical knowledge with teams across the business working on similar services, platforms, and/or products. Forms strategic partnerships with thought leaders in the industry and across domains. Acts as a leading expert in their field for a broad area of research (e.g., Machine Learning, Natural Language Processing, Computer Vision, Statistical Modeling, Data-Driven Insights) and applies relevant research to solve internal or product-related problems. Recognizes the relevant people, organizations, and institutions that will influence the research agenda and competitive landscape within their research area.
- Champions innovative principles and forward-looking technologies related to changes in industry/market trends, advances, and opportunities in applied technologies. Develops and shares new and unique technical knowledge with teams across the business working on similar services, platforms, and/or products. Forms strategic partnerships with thought leaders in the industry and across domains.
- Acts as a leading expert in their field for a broad area of research (e.g., Machine Learning, Natural Language Processing, Computer Vision, Statistical Modeling, Data-Driven Insights) and applies relevant research to solve internal or product-related problems. Recognizes the relevant people, organizations, and institutions that will influence the research agenda and competitive landscape within their research area.
- Machine Learning Functionality, Insights, and Technical Tools Oversees the team to perform machine learning/data extraction, transformation, and loading (ETL) pipelines (e.g., data collection, cleaning) based on data prepared. Guides the architecture of scalable pipelines and datasets across multiple business units. Influences the direction of the team. Anticipates potential data pipeline issues and provides solutions. Collaborates with senior leaders across disciplines. Creates data pipelines to capture metrics and directions of new business branches or products. Builds models with deep understanding of system to be able to create more impact. Leverages understand of domain to train models. Leads team analyzing complex problems by designing, creating, and using state-of-the-art algorithms that structures, analyzes, and uses data in product and platforms for scalable artificial intelligence solutions. Anticipates issues with algorithms and provides suggestions to overcome challenges. Guides the team in identifying and implementing improvement strategies to algorithms. Provides guidance and direction for future stakeholder needs. Maintains deep knowledge of industry trends, technologies, and advances. Builds frameworks that solve problems across diverse problems. Demonstrates deep understanding of the internals of machine learning frameworks. Demonstrates deep expertise in problem domain training.
- Oversees the team to perform machine learning/data extraction, transformation, and loading (ETL) pipelines (e.g., data collection, cleaning) based on data prepared. Guides the architecture of scalable pipelines and datasets across multiple business units. Influences the direction of the team. Anticipates potential data pipeline issues and provides solutions. Collaborates with senior leaders across disciplines. Creates data pipelines to capture metrics and directions of new business branches or products.
- Builds models with deep understanding of system to be able to create more impact. Leverages understand of domain to train models. Leads team analyzing complex problems by designing, creating, and using state-of-the-art algorithms that structures, analyzes, and uses data in product and platforms for scalable artificial intelligence solutions. Anticipates issues with algorithms and provides suggestions to overcome challenges. Guides the team in identifying and implementing improvement strategies to algorithms. Provides guidance and direction for future stakeholder needs. Maintains deep knowledge of industry trends, technologies, and advances. Builds frameworks that solve problems across diverse problems. Demonstrates deep understanding of the internals of machine learning frameworks. Demonstrates deep expertise in problem domain training.
- 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.
- 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.
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.
- 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.
- 3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
- 7+ years experience conducting research as part of a research program (in academic or industry settings).
- 5+ years experience developing and deploying live production systems, as part of a product team.
- 7+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
Tags & focus areas
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