Microsoft’s Cloud business is experiencing explosive growth, and the Capacity, Supply Chain & Provisioning (CSCP) organization is responsible for enabling the infrastructure underlying this growth. Our mission is to deliver the world’s computer with an industry-leading supply chain. CSCP is responsible for strategic sourcing, customer demand forecasting, capacity planning and management, supply chain planning and execution, capacity provisioning, and decommissioning and dispositioning of datacenter assets worldwide.

AHSI's Capacity Supply Chain and Provisioning (CSCP) is looking for a highly motivated data scientist to help us predict, optimize and build the future of cloud computing.

You will operate as part of a well-established data science team within CSCP, responsible for managing data, feature engineering, and model innovation. You will build new models, maintain/enhance production models Your statistical and machine learning models will drive significant investment and supply chain decisions for Microsoft’s vast and rapidly growing cloud business. You will be faced with problems ambiguous in nature and will need to think creatively and practically to develop effective solutions to address them. You will interact closely with fellow data scientists, PMs, engineers, leadership teams and other stakeholders by acting as a subject matter expert in quantitative methods, and will develop models that chart the course of demand for Microsoft’s entire cloud business.

In addition to building data science models, you will provide thought leadership and business insights as needed. The successful candidate will demonstrate business acumen, experience in developing data science models and ability to work effectively with cross functional teams in a fast-paced environment. You should have excellent business and communication skills to collaborate with business owners to support their needs.

Responsibilities

• Researching and developing production-grade models (forecasting, anomaly detection, optimization, clustering, etc.) for our global cloud business by using statistical and machine learning techniques
• Manipulate large volumes of data, create new and improved solutions for data collection, management, analyses, and data science model development
• Drive the onboarding of new data and the refinement of existing data sources through feature engineering and feature selection
• Apply statistical concepts and cutting-edge machine learning techniques to analyze cloud demand
• Optimize our data science model code for distributed computing platforms and task automation
• Work closely with other data scientists and data engineers to deploy models that drive cloud infrastructure capacity planning
• Present analytical findings and business insights to project managers, stakeholders, and senior leadership
• Required to keep abreast of new statistical / machine learning techniques and implement them as appropriate to improve predictive performance

Qualifications

Required

• B.Tech. M.Tech. M.Sc. in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations Research or similar applied quantitative field
• 5-6 years of industry experience in developing production-grade statistical and machine learning code in a collaborative team environment
• Prior experience in machine learning using R or Python (scikit / numpy / pandas / statsmodel)
• Prior experience in time series forecasting
• Prior experience with typical data management systems and tools such as SQL
• Knowledge and ability to work within a large-scale computing or big data context, and hands-on experience with Hadoop, Spark, DataBricks or similar
• Excellent analytical skills; ability to understand business needs and translate them into technical solutions, including analyses specifications and models
• Creative thinking skills with emphasis on developing innovative methods to solve hard problems under ambiguity and no obvious solutions
• Good interpersonal and communication (verbal and written) skills, including the ability to write concise and accurate technical documentation and communicate technical ideas to non-technical audiences

Preferred

• PhD/Graduate degree in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations Research or similar applied quantitative field
• Experience in machine learning using R or Python (scikit / numpy / pandas / statsmodel) with skill level at or near fluency
• Experience with deep learning models (e.g., tensorflow, PyTorch, CNTK) and solid knowledge of theory and practice
• Practical and professional experience contributing to and maintaining a large code base with code versioning systems such as Git
• Knowledge of supply chain models, operations research techniques, optimization modeling and solvers.

CLOUD SCREENING REQUIREMENT:

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. 

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

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