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Start your career by building real-world technology that reaches millions. At Microsoft, you’ll work in a collaborative environment where you can learn quickly and contribute to real projects from the start. As an Applied Scientist, you’ll help bring new ideas and research into production. You’ll work alongside experienced researchers and engineers to turn concepts into working solutions, applying scientific thinking to practical problems. This role is intended for early-career candidates who want to build their skills while contributing to meaningful projects.
Job Responsibility:
Gain an understanding of the latest research related to Microsoft products or business groups and assists in technology transfer attempts, contributing to patents, co-authoring white papers, developing or maintaining tools/services for internal Microsoft use, or consulting for product or business groups
Gain an understanding of a broad area of research (e.g., Machine Learning, Natural Language Processing, Computer Vision, Statistical Modeling, Data-Driven Insights) and the corresponding literature and applicable research techniques
Help reinforce a positive environment by learning and adopting best practices and maintain or develop ties with external network of peers and identify prospective talent for Microsoft research pipelines, when asked
Assist with documentation for senior team members as requested and participate in the creation of informal documentation as well as follow ethics and privacy policies when executing research processes and/or collecting data/information
Prepare data to be used for analysis by reviewing criteria that reflect quality and technical constraints and review data and suggests data to be included and excluded to address data quality problems
Embody our culture and values
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND relevant internship experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field