Microsoft is a global leader in software, services, devices, and solutions that help individuals and businesses realize their full potential.
The role of a Research Scientist at Microsoft involves conducting cutting-edge research in machine learning and artificial intelligence, with a focus on developing innovative solutions and models to tackle complex real-world problems. Key responsibilities include designing and implementing advanced AI/ML systems, creating and refining machine learning models, and collaborating with cross-functional teams to deliver data-driven insights. A successful candidate will possess a strong background in statistics, mathematics, and programming, along with practical experience in machine learning frameworks, data analysis, and model evaluation. Attributes such as a growth mindset, a passion for innovation, and the ability to work collaboratively within diverse teams are essential, aligning with Microsoft's core values of respect, integrity, and accountability.
This guide will help you prepare for your interview by providing insights into the expectations and requirements for the role, allowing you to showcase your skills and experiences effectively.
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How prepared are you for working as a AI Research Scientist at Microsoft?
Typically, interviews at Microsoft vary by role and team, but commonly Research Scientist interviews follow a fairly standardized process across these question topics.
We've gathered this data from parsing thousands of interview experiences sourced from members.
Practice for the Microsoft Research Scientist interview with these recently asked interview questions.
| Question | Topic | Difficulty | ||||||||||||||||||||
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SQL | Medium | |||||||||||||||||||||
Let’s say we have a table representing a company payroll schema. Due to an ETL error, the employees table, instead of updating the salaries every year when doing compensation adjustments, did an insert instead. The head of HR still needs the current salary of each employee. Write a query to get the current salary for each employee. Note: Assume no duplicate combination of first and last names (I.E. No two John Smiths). Assume the Example: Input:
Output:
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Data Structures & Algorithms | Easy | |||||||||||||||||||||
Data Structures & Algorithms | Hard | |||||||||||||||||||||
SQL | Easy | |
Machine Learning | Medium | |
Statistics | Medium | |
SQL | Hard | |
Machine Learning | Medium | |
Python | Easy | |
Deep Learning | Hard | |
SQL | Medium | |
Statistics | Easy | |
Machine Learning | Hard |
Discussion & Interview Experiences