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

Statistics

Without a deep knowledge of statistics, it is difficult to succeed as a data scientist – accordingly, a interviewer will try to test your understanding of the subject with statistics-oriented data science interview questions. Be prepared to answer some fundamental statistical questions as part of your interview.

Machine Learning Systems Design

There are several main headings in this block of questions:

  1. Setting up the project
  2. Data pipeline
  3. Modeling: selection, training and debugging.
  4. Service: testing, deployment and support
    Preparation guide

I wrote the Data Science Interview Guide booklet. Now there is an opportunity to purchase it with a $2 discount using the BLOG promo code, valid until the end of September 2021.

Behavioral

Employers love questions about behavior. They reveal information about the respondent’s experience, behavior, and how this might affect the rest of the team. With these questions, the interviewer wants to see how the candidate has responded to situations in the past, how well they can articulate their role, and what they have learned from their experience.
You may be asked several categories of behavioral questions:

  1. Teamwork
  2. Leadership
  3. Conflict management
  4. Problem solving
  5. Failures
    Before the interview, write down examples of work experience related to these topics to refresh your memory – you will need to remember specific examples in order to answer the questions well.

Culture fit

An employer often tries to figure out where your interest in data science and a hiring company comes from. There is no reason not to be yourself. There are no right answers to these questions, but the best answers are given with confidence.

Problem-Solving

At some point during the interview, interviewers will want to test your problem-solving ability with data science interview questions. Often these tests are an open question: How would you handle X? In general, this X will represent a task or problem specific to the company you are applying to.

A few quick tips: Don’t be afraid to ask questions. Employers want to test your critical thinking skills, and asking questions that clarify points of uncertainty is a trait any data scientist should have. Also, if the problem provides an opportunity to demonstrate your programming skills on a whiteboard or create schematic diagrams, use that to your advantage.

Conclusion

There is no single “best” way to prepare for a data science interview, but hopefully, by learning these common questions for data scientists, you will be able to pass your interview with good practice and confidence. If you have any suggestions for questions, let us know! Good luck.

Useful links

I wrote the Data Science Interview Guide booklet. Now there is an opportunity to purchase it with a $2 discount using the BLOG promo code, valid until the end of September 2021.

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