Microsoft is Hiring Data Science Interns | Apply Now

Overview

Join Microsoft as a University Intern to build community, explore your passions, and contribute your best work. This opportunity allows you to bring your aspirations, talent, potential, and excitement for the journey ahead.

As a Data Scientist Intern at Microsoft, you will utilize machine learning, statistics, experiments, and various other techniques to develop and enhance products, driving business impact. You will collaborate with stakeholders, formulate problem-solving approaches, and apply algorithms and data sources within the context of business and engineering requirements. This role enables you to combine your engineering capabilities with analytical skills to improve customer experiences. Our Data Scientists regularly employ innovative methods, algorithms, and tools to achieve results across Microsoft devices, operating systems, products, and services, providing novel insights into business and customer scenarios.

Interns at Microsoft engage in real-world projects, collaborating with global teams, while enjoying the process. You will be empowered to foster community, explore your passions, and achieve your goals. This is your opportunity to bring your solutions and ideas to life while working on cutting-edge technology.

Responsibilities

• Formulate approaches to solve problems using well-defined algorithms and data sources.
• Incorporate an understanding of product functionality and customer perspective to provide context for these problems.
• Utilize data exploration techniques to uncover new questions or opportunities within your problem area and propose the applicability and limitations of the data.
• Interpret the results of your analysis, validate your approach, and learn to monitor, analyze, and iterate for continuous improvement.
• Engage with peer stakeholders to produce clear, compelling, and actionable insights that influence product and service enhancements, impacting millions of customers.
• Participate in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to enhance the impact and applicability of your results.