Senior Data Scientist

Microsoft Cloud Operations + Innovation (CO+I) is the engine that powers Microsoft’s cloud services. Our team is dedicated to delivering high-quality infrastructure to support cloud operations. As Microsoft’s cloud business continues to mature, our infrastructure expansion accelerates—with Data Centers at the core of this growth. To support this momentum, we are scaling the acquisition and development of our owned, designed, and constructed Data Center facilities. In parallel, we continue to lease and acquire Data Center capacity at pace, especially in high-growth markets. This involves close collaboration with Data Center operators across regions and around the globe.

We are seeking a skilled Senior Data Scientist to join our CO+I Lease and Land Development Digital Transformation team. This role is ideal for someone who thrives in a fast-paced environment, enjoys solving complex problems, and is passionate about using data to influence product strategy and enhance customer experience. You will collaborate with cross-functional teams—including PMs, engineers, and business stakeholders—to deliver AI and Agentic AI solutions, actionable insights, and scalable data systems.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees, we embrace a growth mindset, innovate to empower others, and collaborate to achieve shared goals. Every day, we build on our values of respect, integrity, and accountability to foster a culture of inclusion where everyone can thrive—at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment that positively impacts our culture every day.

Responsibilities

• Apply modification techniques to transform raw data into compatible formats for downstream systems. Utilize software and computing tools to ensure data quality and completeness. Implement code to extract and validate raw data from upstream sources, ensuring accuracy and reliability.
• Writes efficient, readable, extensible code from scratch that spans multiple features/solutions. Develops technical expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects.
• Leverages technical proficiency of big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, continuous integration and continuous delivery (CI/CD), Docker, Delta Lake, MLflow, AML, and representational state transfer (REST) application programming interface (API) consumption/development
• Acquires data necessary for successful completion of the project plan. Proactively detects changes and communicates to senior leaders. Develops usable data sets for modeling purposes. Contributes to ethics and privacy policies related to collecting and preparing data by providing updates and suggestions around internal best practices. Contributes to data integrity/cleanliness conversations with customers
• Adhere to data modeling and handling procedures to maintain compliance with laws and policies. Document data type, classifications, and lineage to ensure traceability and govern data accessibility.
• Perform root cause analysis to identify and resolve anomalies. Implement performance monitoring protocols and build visualizations to monitor data quality and pipeline health. Support and monitor data platforms to ensure optimal performance and compliance with service level agreements.
• Knowledge and implementation of an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
• Leverages knowledge of machine learning solutions (e.g., classification, regression, clustering, forecasting, NLP, image recognition, etc.) and individual algorithms (e.g., linear and logistic regression, k-means, gradient boosting, autoregressive integrated moving average [ARIMA], recurrent neutral networks [RNN], long short-term memory [LSTM] networks) to identify the best approach to complete objectives. Understands modeling techniques (e.g., dimensionality reduction, cross validation, regularization, encoding, assembling, activation functions) and selects the correct approach to prepare data, train and optimize the model, and evaluate the output for statistical and business significance. Understands the risks of data leakage, the bias/variance tradeoff, methodological limitations, etc.
• Writes all necessary scripts in the appropriate language: T-SQL, U-SQL, KQL, Python, R, etc. Constructs hypotheses, designs controlled experiments, analyzes results using statistical tests, and communicates findings to business stakeholders. Effectively communicates with diverse audiences on data quality issues and initiatives. Understands operational considerations of model deployment, such as performance, scalability, monitoring, maintenance, integration into engineering production system, stability. Develops operational models that run at scale through partnership with data engineering teams. Coaches less experienced engineers on data analysis and modeling best practices. Develops a strong understanding of the Microsoft toolset in artificial intelligence (AI) and machine learning (ML) (e.g., Azure Machine Learning, Azure Cognitive Services, Azure Databricks).
• Design and Implement Dashboards: Develop user-friendly dashboards for various applications, such as Supplier Spend Analytics, Supplier Scorecards, Incident and Service Level Agreement (SLA) Compliance Monitoring, Spares and Inventory Management, and other business-facing applications.

Qualifications

Required Qualifications:

• Bachelor’s or Master’s degree in computer science, Math, Software Engineering, Computer Engineering
• Excellent analytical skills with a systematic and structured approach to software design
• 5+ years of experience in data science, analytics, or machine learning
• 4+ years of experience in developing solutions with Microsoft Power Platform (Power BI, Fabric, Power Automate & M365 Dataverse).
• 3+ years of experience in building Data Pipelines using Azure Data Factory.
• 1+ year of experience in developing solutions in Azure Fabric
• 4+ Years of experience in writing SQL Queries
• Experience with data cloud computing technologies such as – Azure Synapse, Azure Data Factory, SQL, Azure Data Explorer
• or related field AND 4+ years’ experience in business analytics, data science, data modeling, or data engineering.

Preferred Qualifications:

• 8+ years of experience in data engineering with proven coding and debugging skills in C#, Python, and/or SQL
• Creative problem-solving & analytical skills to drive keen insights and identification of opportunities combined with a “sense of urgency” to develop solutions.
• Deploying solutions in Azure Services & Managing Azure Subscriptions
• Understanding and knowledge about big data and writing queries with Kusto/KQL.
• Understanding and knowledge about extracting data via REST APIs
• Excellent analytical skills with a systematic and structured approach to software design

Background Check Requirements:

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.

#COICareers | #EPCCareers | #DCDCareers

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until October 13, 2025.

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.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.