Microsoft has been a big player in the data science industry after Azure, and its machine learning tools have been slowly dominating as the biggest service provider in the cloud-computing market. As a result, Microsoft has been building out its data science team slowly but surely over the past five years to become one of the biggest companies hiring for the role.
A Microsoft Data Scientist role varies greatly and depends on whichever team you’ve been interviewed Each Microsoft data science job is different and spans from analytics-based roles to more machine learning heavy. As a huge multi-conglomerate corporation, Microsoft has different teams that work on speech and language, artificial intelligence, machine learning infrastructure on Azure, a Data Science consulting for cloud computing, and much more.
Microsoft generally prefers to hire experienced candidates with about a minimum of 2+ years of experience working in data science for a mid-level role. General qualifications are a Ph.D. in a quantitative field and some years of experience in any one of these fields (DNN, NLP, time series, reinforcement learning, network analysis, or causal inference).
Microsoft has a department under engineering called data and applied science. Employees in this department are often placed in teams and go by three main titles: Data scientists, applied scientists, and machine learning engineers. Depending on the team, their functions would include:
After submitting your application for the job, the first phone interview may or may not be with a recruiter depending on the seniority level of the role. The hiring manager will often conduct a 30-minute interview first to understand your past experience.
Expect this part of the phone interview to come in two parts. You will be asked about your background and projects, as well as a few technical interview questions. The technical Data Science interview questions will be more theoretical along the lines of explaining how a machine learning concept works or a quick probability or statistical problem.
Examples:
After the hiring manager screen, the recruiter will schedule a second more technical screen with a Microsoft data scientist. Generally, this screen is 45 minutes to an hour and designed to test pure technical skills and how well you can code and explain your thought process.
The technical screen consists of around three different questions covering the topics of algorithms, SQL coding, and probability and statistics. Expect questions akin to data structures and algorithms in Python along with data processing type questions.
Examples:
The onsite interview consists of a full day event from 9 am to 4 pm. You will meet with five different data scientists and go on a lunch interview as well.
Here’s what the interview panel generally looks like:
The onsite interview will be mostly a combination of all the different technical concepts. Remember to study different model assessment metrics in different circumstances, the bias/variance tradeoff of coefficients under collinearity, open-ended questions about sampling schemes, experimental and ab testing design, explaining p-values to a 5 year old, different concepts of Bayes theorem, and teaching the interviewer a statistical learning technique of your choice.
Another big focus for Microsoft is on communication, since the data science team at Microsoft has partnerships throughout the organization to ensure the team is doing useful work.
You can find many data structures and algorithm questions on Interview Query or Leetcode. It’s also advisable to get a whiteboard to practice writing code on, given how different coding on a whiteboard versus the computer.
Here are some questions that may get asked in your Microsoft Data Science Interview:
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