Notes about Machine Learning, Data Science and Analytics Engineering

How to prepare for a data science interview

Data science interview is not easy. There is considerable uncertainty about the issues. Regardless of what kind of work experience you have or what kind of data science certification you have, the interviewer may be throwing you a series of questions that you weren’t expecting. During a data science interview, the interviewer will have technical questions on a wide range of topics, requiring the interviewee to have both strong knowledge and good communication skills.

In this note, I would like to talk about how to prepare for a machine learning science / interview date. We will sort out the categories of questions, I will share links with questions and answers to frequently asked questions.

Question categories

Traditionally, data science / machine learning interviews include the following categories of questions:

  1. Statistics
  2. Machine learning algorithms
  3. Programming skills, algorithms and data structures
  4. Knowledge of the domain area
  5. Machine Learning Systems Design
  6. Behavioral
  7. Culture Fit
  8. Problem-Solving

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How to make your CV attractive with a pet project

For junior Date Scientists, a CV consists of courses taken, education, and possibly not the most relevant work experience. Such resumes are not much different from the bulk of job seekers.

Working on a pet project is a great opportunity to improve skills. If you add the implemented pet-project to the CV, it will immediately become attractive and a topic for conversation at the interview will appear.

So what is a pet-project? Pet-project is a project that is done for yourself. It is created outside of work and is often self-interested. For example: sports, electronics, food preparation, auto, travel, medicine, etc. The project will help expand professional skills and learn new ones that will be useful in work.

Here are some ideas for projects in Data Science that you can get started with:

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