Senior Applied Scientist

Overview

Are you ready to help shape the future of artificial intelligence for cloud operations (Artificial Intelligence for Operations, or AIOps)? The Azure Artificial Intelligence for Operations team at Microsoft is focused on advancing how artificial intelligence supports Microsoft and Azure engineers in building and operating high-quality services with greater efficiency and reliability.

In this Senior Applied Scientist role, you will collaborate with scientists and engineers to apply advanced machine learning and artificial intelligence techniques to challenges in cloud reliability, scalability, and automation. Your work will influence how Microsoft delivers secure, resilient, and innovative cloud solutions to customers around the world.

As a Data Science IC4, you will design, implement, and optimize artificial intelligence models built for large-scale cloud environments. This includes developing deep learning architectures, experimenting with new algorithms, and contributing to production-ready solutions that support automated detection, diagnosis, and remediation of service issues, as well as predictive capabilities that help prevent potential outages.

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.

Responsibilities

• Identify and define business problems in cloud operations that can be addressed using artificial intelligence and machine learning (AI/ML), drafting proposals that articulate urgency, scenarios, and success criteria before proceeding with model development.
• Design, implement, and optimize state-of-the-art artificial intelligence (AI) models for large-scale Microsoft Azure cloud operations, focusing on reliability, scalability, and automation.
• Develop proof-of-concept (POC) models within time-bounded cycles, ensuring rapid iteration and fail-fast learning to validate technical approaches and business impact.
• Collaborate with engineering, research, and product teams to integrate AI/ML models into end-to-end Azure AIOps product solutions, ensuring seamless deployment and operationalization.
• Contribute to build and maintain robust machine learning (ML) infrastructure, including model hosting, training, inference, validation, and data pipelines, to support scalable and reliable production environments.
• Apply advanced deep learning techniques and experiment with novel algorithms to automate detection, diagnosis, and remediation of service issues, as well as to enable predictive capabilities that prevent outages.
• Ensure all solutions adhere to Microsoft’s Responsible Artificial Intelligence (AI) principles, including ethical standards, inclusivity, and compliance with governance policies.

Required Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)OR equivalent experience.

Other Requirements

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)OR equivalent experience.

Key skills/competency

• Artificial Intelligence
• Machine Learning
• Cloud Operations (AIOps)
• Deep Learning
• Cloud Reliability
• Scalability
• Model Optimization
• Data Pipelines
• Predictive Analytics
• Ethical AI