Data & Applied Scientist II at Microsoft

, , India -

Full Time

Start Date

Immediate

Expiry Date

05 Mar, 26

Salary

0.0

Posted On

05 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Operations Research, Optimization Algorithms, Software Engineering, Capacity Planning, Inventory Optimization, Simulation, Mathematical Programming, Machine Learning, Distributed Computing, Python, R, Java, C#, SQL, Cloud Architecture

Industry

Software Development

Description

Overview Microsoft’s Cloud business is expanding rapidly, and the Cloud Supply Chain (CSCP) organization is responsible for enabling the hardware infrastructure that powers this growth — including AI. CSCP’s vision is to empower customers to achieve more by delivering Cloud and AI capabilities at scale, and its mission is to deliver the world’s computer with an industry-leading supply chain. In addition to traditional supply chain functions such as plan, source, make, and deliver, CSCP also manages supportability (spares), sustainability, and global decommissioning of datacenter assets. We deliver the core infrastructure and foundational technologies for more than 200 Microsoft online businesses — including Bing, Office 365, Xbox Live, OneDrive, and the Azure platform — serving over 1 billion customers in 90+ countries through 300+ datacenters worldwide. The Microsoft Capacity Planning (MCP) team within CSCP is tasked with planning all aspects of capacity across the Azure fleet. Our aspiration is to provide fully automated and highly optimized capacity planning systems. As a member of MCP, you will collaborate with engineers, program managers, and planners across CSCP, translating business problems into scalable solutions and driving them end-to-end from design to production. You will also contribute to strategic decisions for all capacity-impacting features. We are seeking a talented Data Scientist to develop and apply advanced methods in operations research, stochastic optimization, simulation, and large-scale mathematical programming, augmented by core computer science disciplines such as algorithms, data structures, and distributed computing. Your work will focus on capacity planning, inventory optimization, and scenario analysis, designing research-driven models to solve complex challenges in cloud supply chain planning. The impact of your work will be measured through improvements in Azure capacity fulfillment, platform efficiency, COGS reduction, and customer satisfaction. Our team partners closely with engineering, applying state-of-the-art machine learning and constrained optimization techniques to some of the most complex real-world problems at scale. If you are excited by cutting-edge methods and their application in a dynamic, global environment, you will thrive on our team as we deliver world-class innovation. Responsibilities Develop optimization algorithms and production-grade libraries, conduct experiments to support planning and execution in Microsoft’s Cloud Supply Chain business. Apply best practices in data science, software engineering, and operations research to deliver impactful solutions. Drive improvements to the design, architecture, and user experience of Microsoft first-party planning tools, enhancing the productivity of Cloud Supply Chain Planners. Collaborate with cross-functional teams to improve platform manageability and influence strategic decisions for capacity-impacting features. Contribute to team culture and apply engineering and data science best practices in daily work. Apply best practices in data science, software engineering, and operations research to deliver impactful solutions. Qualifications Master’s in Data Science, Computer Science or related field with specialization in Operation Research. 3+ years of hands-on experience solving planning and optimization problems in supply chain domains such as capacity planning, inventory optimization and buffer planning. Strong computer science foundation with experience in designing and building production-grade algorithms, and systems. Azure Cloud Services development experience, or related. Proficiency in programming languages such as Python, R, Java, C#, etc., and experience with relational databases (Kusto, SQL ). Solid understanding of modern cloud architecture and technologies. A proven track record of collaborating across organizational boundaries and delivering great results. Demonstrated ability to think from first principles and translate complex business problems into scalable technical solutions. Comfortable working across the boundaries of data science, operations research, and software engineering. Additional or Preferred Qualifications (PQs): Doctoral degree in Data Science, Computer Science, Operations Research, or a related field. Published research in leading operations research journals (e.g., INFORMS). Proven track record in building commercial-grade inventory optimization software. Experience conducting UX research to inform product and system design. Experience with globally distributed cloud systems, with emphasis on quality, scalability, and reliability. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Develop optimization algorithms and production-grade libraries to support planning and execution in Microsoft’s Cloud Supply Chain. Collaborate with cross-functional teams to improve platform manageability and influence strategic decisions for capacity-impacting features.