Senior Data Scientist

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Microsoft’s Cloud business is expanding, and the Cloud Supply Chain (CSCP) organization is responsible for enabling the infrastructure underlying this growth including AI! CSCP’s vision is to empower customers to achieve more by delivering Cloud Capacity Differentiated at Scale. Our mission is to deliver capacity for all cloud services predictably through intelligent systems driven by continuous learning and a world class organization. The CSCP Organization is responsible for traditional supply chain functions such as Plan, Source, Make, Deliver, but also manages supportability (spares), decommissioning and disposition of Data center assets worldwide. We deliver the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Skype, OneDrive and the Microsoft Azure platform for external customers. Our infrastructure is comprised of a large global portfolio of more than 200 datacenters supporting services for more than 1 billion customers in over 90 countries worldwide.

Microsoft Cloud Planning (MCP) is one of the most central functions within CSCP due to its direct impact on Microsoft cloud business success. This team forecasts, plans and manages the majority of Microsoft’s cloud services and directly influences cloud user experience. This is a central function that closely partners with Engineering, Product, Finance, Supply Chain, Data Centers, NPI and Deployment Engineering. The Data Science team in MCP is growing fast to get ahead of the Cloud Supply chain demand increase and set up practices for forecasting, and prediction.

Minimum Qualifications

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

Preferred Qualifications

• 12+ years of industry in delivering production-grade solutions leveraging statistics, operations research and ML, managing structured and unstructured data, and reporting results.
• Excellent analytical skills; ability to understand business needs and translate them into technical solutions, including analysis specifications and models.
• Creative thinking skills with emphasis on developing innovative methods to solve hard problems under ambiguity and no obvious solutions.
• Prior experience in time series forecasting, and/or operations research
• Prior experience in Machine Learning using Python/R (scikit/numpy/pandas/statsmodel), hands-on experience with Hadoop, Spark, Databricks or similar
• 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.
• PhD in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations Research or similar applied quantitative field.
• Knowledge of supply chain models, operations research techniques, optimization modelling and solvers.
• 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.

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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.

Responsibilites

• Strategic Planning and Risk Mitigation: Drive clarity and understanding of requirements to achieve operational plans, including promotions, sales resources, collaborative planning, forecasting, replenishment (CPFR), budget, and engineering changes. Assess and mitigate potential risks and issues to ensure alignment with business objectives.
• Model Research and Development: Research and develop production-grade models for operations research, inventory optimization, forecasting, anomaly detection, and clustering. Apply statistical, machine learning, and optimization techniques to address complex supply chain challenges and drive impactful business outcomes.
• Data Management and Feature Engineering: Manage large volumes of structured and unstructured data, creating improved processes for data collection, management, and analysis. Drive feature engineering and selection to enhance model performance for forecasting, inventory optimization, and demand planning.
• Optimization and Solver Expertise: Leverage optimization modeling, operations research techniques, and solvers to develop actionable solutions for supply chain challenges, including inventory management, replenishment, and capacity planning. Consistently apply algorithmic techniques to optimize solutions for real-world business scenarios.
• Collaboration and Innovation: Lead cross-functional collaboration to identify opportunities for state-of-the-art algorithm application in solving supply chain and demand planning problems. Guide teams in using data-driven insights to uncover trends and recommend strategies for optimization.
• Forecasting and Demand Planning: Oversee the creation and refinement of short- and long-term demand forecasts. Analyze forecast accuracy metrics, identify potential sources of error, and implement advanced statistical models to improve forecast precision and reliability.
• Advanced Analysis and Troubleshooting: Modify and enhance statistical and machine learning tools for evaluating optimization and inventory models. Solve challenging problems related to data quality, model performance, and ambiguous business requirements by leveraging expertise in operations research and supply chain management.
• Communication and Leadership: Present analytical findings and business insights to stakeholders and senior leadership. Serve as a mentor to team members, providing guidance on the application of optimization and machine learning techniques within a supply chain context.
• Governance and Process Improvement: Advocate for continuous improvement by leading governance processes and fostering cross-group collaboration to address current and future supply chain needs. Ensure the incorporation of best practices and business drivers into operational plans.
• Thought Leadership: Stay updated on the latest advancements in machine learning, optimization, and supply chain strategies. Evangelize the adoption of cutting-edge methodologies to improve predictive and prescriptive capabilities, ensuring alignment with organizational goals. Project Management and Delivery: Independently manage projects, track timelines, and ensure the delivery of high-quality outcomes. Establish clear milestones, monitor progress, and proactively address challenges to meet business objectives.