Overview

Microsoft’s Cloud business is expanding, and the Cloud Supply Chain (CSCP) organization is responsible for enabling the hardware infrastructure underlying this growth including AI! CSCP’s vision is to empower customers to achieve more by delivering Cloud and AI capabilities at scale. Our mission is to deliver the world's computer with an industry-leading supply chain. The CSCP organization is responsible for traditional supply chain functions such as plan, source, make, deliver, but also manages supportability (spares), sustainability, and decommissioning of datacenter assets worldwide. We deliver the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, OneDrive and the Microsoft Azure platform for external customers. Our infrastructure is supported by more than 300 datacenters around the world that enable services for more than 1 billion customers in over 90 countries.

The Cloud Supply Chain Engineering (CSCP-E) group is an exciting and fast-evolving engineering group within Microsoft that powers Microsoft’s Cloud-first mission. We are responsible for supporting the supply chain that powers Microsoft's cloud infrastructure. This is a great opportunity to join a dynamic team and influence the way one of the world’s largest and fastest growing cloud environments is built and supported.

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.

#CSCP #CSCPJobs

Responsibilities

Design and implement advanced optimisation algorithms (linear programming, mixed-integer programming, constraint optimisation, heuristics) to solve large-scale decision-making problems such as resource allocation and supply chain planning. Develop mathematical and statistical models leveraging traditional machine learning techniques (classification, regression, clustering) and deep learning for predictive and prescriptive analytics. Collaborate with engineering, product, and research teams to integrate optimisation and ML solutions into scalable production systems. Analyse large datasets to identify patterns, constraints, and insights, translating them into optimisation objectives and ML features. Build and deploy end-to-end pipelines for machine learning and optimisation workflows using modern frameworks and cloud platforms. Ensure solutions meet organisational standards for performance, scalability, and reliability. Explore hybrid approaches combining optimisation with AI/ML techniques to drive innovation. Champion best practices for modelling, experimentation, and deployment while influencing cross-functional teams.

Qualifications

Minimum Qualifications:

Bachelor’s or Master’s degree in Operations Research, Applied Mathematics, Computer Science, Data Science, or related quantitative field.

12+ years of experience delivering AI/ML and optimisation solutions, including modelling, algorithm design, and deployment.

Strong expertise in optimisation techniques: linear programming, integer programming, constraint satisfaction, stochastic optimisation.

Proficiency in optimisation libraries and solvers (e.g., Gurobi) and programming languages such as Python or R.

Hands-on experience with traditional ML frameworks (scikit-learn, TensorFlow, PyTorch) and statistical modelling.

Familiarity with data management systems (SQL) and big data platforms (Spark, Databricks).

Experience with cloud-based MLOps workflows (Azure ML Ops, Azure AI Studio).

Excellent collaboration and communication skills to influence and work effectively with cross geo-teams.Strong problem-solving abilities and strategic thinking to drive innovation.

Preferred Qualifications

Experience in AI product integration and deployment at scale.Familiarity with time series forecasting and advanced statistical modelling.

Knowledge of supply chain models and demand forecasting is a plus.Practical experience with large-scale codebases and version control systems (e.g., Git).

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.

Senior Data and Applied Scientist