Data & Applied Scientist at Microsoft

Short Description:

Microsoft's CSCP organization, amid the Cloud business's growth, seeks dynamic individuals for the Spares Supply Chain team. The role involves developing reporting capabilities, ETL strategy ownership, and fostering agile practices. Candidates should leverage supply chain expertise, collaborate on the Spares & Warranty Pulse, and contribute to continuous improvement initiatives.

Overview:

Microsoft's Cloud business is currently experiencing remarkable growth, and the Capacity, Supply Chain & Provisioning (CSCP) organization plays a pivotal role in enabling the infrastructure supporting this expansion. Our mission revolves around delivering the world's leading supply chain to power the globe's computing needs. CSCP is entrusted with strategic sourcing, customer demand forecasting, capacity planning and management, supply chain coordination, capacity provisioning, as well as datacenter asset decommissioning and dispositioning on a global scale.

Within the Azure Hardware Systems & Infrastructure, the Spares Supply Chain team holds responsibility for ensuring precise placement and availability of spare parts worldwide, precisely aligning with global capacity requirements. SWOPs is currently undergoing a supply chain transformation to efficiently manage spares and warranty aspects from a serviceability and cost perspective.

We are actively seeking dynamic individuals driven by a passion for harnessing data to enhance customer experiences and elevate business performance.

Responsibilities:

Create robust reporting and insights capabilities while facilitating self-service reporting for essential business performance metrics.
Apply agile development principles to ensure the continuous delivery of value and adaptability to evolving needs.
Collaborate in developing the CPOD Spares & Warranty Pulse as the intelligent control center for Spares & Warranty operations.
Take ownership of the ETL strategy and execution, integrating data from various diverse sources.
Leverage profound supply chain expertise to proactively gather, analyze, and provide insights driving improvements in service parts business performance.
Employ pattern-based analysis to unveil hidden data patterns, unlocking fresh insights for optimizing business performance.
Maintain and manage a SQL-on-Azure instance to support data aggregation and generate over 100 reports.
Actively participate in a bi-weekly scrum process, delivering prioritized and ad-hoc features related to reporting and analysis.
Forge strong cross-discipline and cross-team relationships internally.
Utilize extensive SQL and PowerBI expertise, along with other pertinent tools and technologies, for rapid ad-hoc insights catering to CVP-level audiences.
Engineer, implement, and refine process and tool models to enhance operational efficiency and scalability for service parts operations by offering insightful inputs for prompt and measurable improvements in key performance indicators.
Design, develop, and document architectural solutions and processes.
Pioneer the development of next-generation analytics and statistical models to support a 10x growth in throughput while simultaneously reducing cycle time and variation. Proactively identify opportunities for continuous deployment process improvements and take the lead in driving related initiatives.
Design, develop, and maintain data pipelines, backend, and frontend services to support reporting, monitoring, analysis, and related functions.

Qualifications:

Required Qualifications:

Bachelor of Science degree in quantitative fields like Engineering, Computer Science, and Statistics.
A total of 6+ years of combined experience encompassing Data Science, Program Management, Software Development, technical/engineering roles, demonstrating proficiency in R/Python, PowerBI, SQL, or equivalent technologies.
Proven experience in Data Engineering workloads.

Preferred Qualifications:

Experience in supply chain analytics and modeling techniques.
Familiarity with big data technologies such as Azure Data Lake, Databricks, Hive, Spark, or Scope.
Strong knowledge of data science with hands-on experience in Azure Machine Learning.
Proficiency in developing and deploying ML models to address real-world challenges.
Familiarity with SAP ECC, OER, IBP modules is a plus.
Background in the High-tech Supply Chain, Reverse Logistics, or Service Parts industry is advantageous.

Job Details:

Job Number: 1633781
Work Site: Microsoft on-site only
Travel: 0-25%
Role Type: Individual Contributor
Profession: Research, Applied, & Data Sciences
Discipline: Data & Applied Sciences
Employment Type: Full-Time

Please click here to apply.

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