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Online coding test: At the first stage, you will be asked to complete an online coding assessment. The tasks in the test cover basic coding, algorithms, and data structures. You should understand the concept of algorithm complexity and know about sorting, binary search, dynamic programming, basic data structures, and divide-and-conquer techniques. There is no need to learn complex algorithms for the test. If you do know some of the more advanced algorithms, we will definitely enjoy discussing them during interviews.

Tip: Besides assessing the correctness of your solutions, we are also looking at performance, so try to submit as efficient a solution as possible. The platform for online coding test uses similarity checks, so try to come up with solutions on your own.

Interviews: The second stage is an interview round, which typically consists of four interviews within the same day (45-55 minutes each) with Software Engineer colleagues from different engineering teams. On the technical side, expect algorithms and data structures, coding, architecture, and systems design, as well as problem-solving in general. The interviews will also include other non-technical competency questions, as well as questions about your resume.

Tip: We are here to help you perform your best in the interviews. Before the interviews, feel free to ask your recruiter about how to prepare. During the interviews, ask for clarification and listen to feedback and comments from your interviewers; they may be giving you valuable hints.

Feedback: After the interviews, you can expect to receive feedback on the outcome and our decision. If it is a positive one, this is the point when we will discuss the offer to join the team.

Tip: In case you don’t pass the interviews, you are welcome to apply again. While there are no strict limitations, we usually recommend taking 6-12 months to prepare before reapplying.

Screening interview: At the first stage, you will have a 45-minute screening interview with one of our Product Manager colleagues. The goal is to get to know the key points of your experience and interests so far and assess how this corresponds to the PM role.

Tip: This interview is also your first opportunity to get better insight and understanding of the PM role, so feel free to ask questions.

Interviews: The second stage is an interview round, which typically consists of four interviews within the same day (45-55 minutes each), one with a Software Engineering colleague and the other three with Product Managers. On the technical side, expect some questions covering the fundamentals of computer science, coding, and engineering expertise, but even more role-specific tasks and cases, covering topics such as product design or feature prioritization. The interviews will also include other non-technical competency questions, as well as questions about your resume.

Tip: We are here to help you perform your best in the interviews. Before the interviews, feel free to ask your recruiter about how to prepare. During the interviews, ask for clarification and listen to feedback and comments from your interviewers; they may be giving you valuable hints.

Feedback: After the interviews, you can expect to receive feedback on your performance and our decision. If it is a positive one, this is the point when we will discuss the offer to join the team.

Tip: In case you don’t pass the interviews, you are welcome to apply again. While there are no strict limitations, we usually recommend taking 6-12 months to prepare before reapplying.

Screening interview: At the first stage, you will have a 30-minute screening interview with one of our Data Scientist colleagues. The goal is to get to know the key points of your experience and interests so far and assess how this corresponds to the Data Scientist role.

Tip: This interview is also your first opportunity to get better insight and understanding of the role, so feel free to ask questions.

Interviews: The second stage is an interview round, which typically consists of 4 interviews within the same day (45-55 minutes each) with Software Engineer and Data Scientist colleagues from one or more of our engineering teams. You can expect some questions covering the fundamentals of computer science, coding, and engineering expertise. On a more role-specific side, the topics will depend on the attributes of the open position:

- For roles involving statistic modeling, be prepared to dive into questions on general mathematics and statistics, data manipulation, as well as general knowledge and experience in classic machine learning.

- For roles focused on natural language processing or computer vision, the aim of the interview would be to understand your expertise in these areas, so most of the interviewers will try to delve deep with questions on basic and advanced NLP or CV algorithms.

The interviews will also include other non-technical competency-based questions, as well as questions about your resume.

Tip: We are here to help you give your best in the interviews. Before the interviews, feel free to ask your recruiter about how to prepare. During the interviews, ask for clarification and listen to feedback and comments from your interviewers; they may be giving you valuable hints.

Feedback: After the interviews, you can expect to receive feedback on your performance and our decision. If it is a positive one, this is the point when we will discuss the offer to join the team.

Tip: If you don’t pass the interviews, you are welcome to apply again. While there are no strict limitations, we usually recommend taking 6-12 months to prepare before reapplying. We recommend taking 6-12 months to prepare before reapplying.

Q. What is Data Collection and Labeling?
A. MDCS is developing software for different machine learning algorithms: optical character recognition, document layout analysis, and image analysis. An essential part of this development process is collecting and labeling data samples used for training and testing these algorithms.

For example, images are made of pixels without any information about what they represent. Characters, shapes, or other various features may be of interest. These algorithms are developed to extract and process them in some way, like recognizing text in the case of optical character recognition.

Documents, images, and other file types required by your assigned task are collected (online, scanning, photographing) and then processed manually using specific software.

Q. What do I need to know to be able to do Data Collection and Labeling?
A. No previous experience apart from general computer literacy is needed. All new Data Collection and Labeling Associates will have learning materials available and a mentor to teach them how to label, mark and tag features or properties of the content of the files by using various project-specific applications and tools.

Q. What skills does general computer literacy include?
A. You should be comfortable using Microsoft Office tools like Word, Excel, and PowerPoint and email clients like Outlook. Also, Internet browsing, usage of search engines like Google or Bing, and some basic file management like creating/deleting/copying/pasting/archiving files and folders, and creating and editing text files are required.

Q. I am looking for a new engineering/non-engineering career opportunity. Should I apply for a DC&L associate position?
A. No, the Data collection and labeling position is a temporary and periodical job position for students, not an engineering/non-engineering apprenticeship or internship, and it is not meant to be a career builder. If you are interested in an engineering/non-engineering career at MDCS, please look at our open internships and job positions.

Q. I study tech/I do not study tech. Should I apply for DC&L associate?
A. Different data collection and labeling positions have different requirements and responsibilities, and we are looking for students with both technical and non-technical backgrounds. If you believe you meet the requirements for the DC&L position and would like to have the responsibilities listed there, please feel free to apply.