New 
Sr. Data Scientist
 Microsoft | |
remote work
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 United States, Texas, Irving | |
| 7000 State Highway 161 (Show on map) | |
 Sep 04, 2025 | |
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OverviewAre you excited by the intersection of software engineering and data science? Do you thrive in solving complex problems with data-driven solutions? If so, our team is the right place for you. We're looking for a Senior Data Scientist who is passionate about building robust systems that turn data into actionable insights and enable business transformation through intelligent applications. As a Senior Data Scientist on our team, you will design, build, and maintain scalable software solutions that support data science initiatives across the organization. You'll work closely with data scientists, Machine Learning (ML) engineers, and product teams to enable experimentation, optimize workflows, and bring models into production.This opportunity will allow you to deepen your understanding of machine learning infrastructure, expand your expertise in data-centric development, and accelerate your growth as a hybrid technical contributor in both software engineering and data science. We offer flexible work arrangements and support partial to full remote work, depending on business needs and team alignment. 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.
ResponsibilitiesDesign, develop, test, and maintain scalable software systems that enable data science workflows, including data ingestion, transformation, feature engineering, and model deployment. Collaborate cross-functionally with data scientists, machine learning engineers, product managers, and other software engineers to integrate intelligent solutions into production environments. Build and optimize data pipelines, Application Programming Interfaces (APIs), and tools that support experimentation, automation, and reproducibility in machine learning development. Ensure software quality, security, and compliance through robust testing, code reviews, and adherence to engineering best practices. Leverage telemetry and logging to monitor system health, debug issues, and improve performance. Contribute to architectural decisions and long-term technical strategy for data-driven applications.Stay current with emerging technologies and best practices in software engineering, data science, and machine learning infrastructure. | |