Data Scientist

The MCAPS AI Transformation (AIT) organization is at the forefront of Microsoft’s mission to accelerate AI-driven business value for customers and partners. As a Data Scientist in MCAPS AIT, you will join a dynamic team dedicated to building innovative AI and ML solutions that enrich employee experiences, reinvent customer engagement, and reshape business processes. You will be responsible for designing, developing, and maintaining AI/ML solutions and data products to support  our business goals. You will work in a collaborative, growth-mindset environment, leveraging Microsoft’s cutting-edge AI stack—including Copilot, LLMs, and cloud-native technologies—to deliver scalable, secure, and high-impact products. The ideal candidate will have a strong background in data science, be detail-oriented, and possess excellent problem-solving skills. Our data scientists are empowered to experiment, learn, and drive measurable impact across Microsoft’s global commercial ecosystem.

Responsibilities

• Design, develop, and deploy robust AI/ML models that support business objectives.
• Conduct exploratory data analysis and communicate findings to stakeholders.
• Collaborate with cross-functional teams—including product managers, data scientists, data engineers and UX designers—to deliver end-to-end features from concept to production.
• Participate in code reviews, architecture discussions, and contribute to data science and engineering best practices.
• Assist in building and maintaining models and data science pipelines for MCAPS business units.
• Write well-documented, high-quality, and maintainable code.
• Ensure solutions adhere to Microsoft’s Responsible AI principles, compliance, and security standards.
• Contribute to a culture of inclusion, innovation, and technical excellence within the AIT organization.

Qualifications

Basic Qualifications

• Master’s degree in Computer Science, Engineering, or a related technical field wih a miniumum 3 years' experience and at least 2 years' in Data Science.
• Strong programming skills in Python, SQL, PySpark and proficiency in data science libraries (e.g., scikit-learn, pandas, NumPy).
• Mastery of machine learning fundamentals and statistical modelling.
• Knowledge of LLMs and Azure AI stack / services including Azure AI Foundry and Copilot Studio.
• Strong problem-solving skills and a passion for learning new technologies.
• Demonstrated ability to leverage AI tools (e.g., GitHub Copilot, Azure AI Foundry) for code generation, automation, and productivity enhancement.
• Ability to work collaboratively in a team environment and communicate technical concepts clearly.
• Demonstrated ability to drive innovation and deliver results in a fast-paced environment.

Preferred Qualifications

• Proficiency in multiple programming languages and development frameworks. 
• Familiarity with DevOps practices, CI/CD pipelines, and Infrastructure as Code.
• Familiarity with version control systems (e.g., Git). 
• Experience with Generative AI and familiarity with Microsoft’s AI ecosystem and tools such as Copilot Studio.
• Knowledge of security, compliance, and Responsible AI principles in software development.
• Experience with Azure cloud platform and building distributed systems or web services.

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.

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

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