What To Expect In A Data Science Behavioral Interview
Data Science interview processes can vary depending on the company and industry domain you are applying to. Typically, they start with a behavioral interview with the Hiring Manager or an HR member followed by a technical interview with the team leader and then a coding test and another technical interview with your future team members. This can vary from one company to another, however, a common first step in the hiring process is the behavioral interview. You can know more about the hiring process of data science in this article:
A behavioral interview is a job interviewing technique where candidates are asked to describe past performance and behavior to determine whether they are suitable for a position. The main goal is to know the type of person you are and to see whether you will be a fit with the company culture, core values, and team members and whether you will satisfy their vision and goals or not.
The main goal of a behavioral interview is to evaluate your behavior and performance based on your experience and determine whether this will fit the company’s culture and values or not. This is done through different types of questions which can be categorized into three categories: personal questions, questions about the company’s culture, and situational questions.
Table of content:
- Personal Questions
- Questions About The Company & Role
- Situational Questions
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1. Personal Questions
The first type of behavioral interview question is the personal-based questions. These questions will focus mainly on you to know more about your experiences and personality.
The goal of these questions is to know whether you meet the requirements for the job or not and to know more about your values, work cultures, and soft skills such as communication skills, leadership, time management, values, and passion and to decide whether your personality will fit with the company’s culture, vision and mission.
Here is a list of famous personal questions:
1. Tell us more about yourself?
2. Describe an impactful project that you are proud of
3. How do you approach problems? What’s your process?
4. What’s the best idea you’ve come up with on a team-based project?
5. Are you better at working in a team or on your own?
6. Give me an example of when you set a goal and how you achieved it.
7. How do you juggle multiple projects?
8. Tell me about a time when you worked well under pressure.
9. Where do you see yourself in five years and how the company and the role will help you to reach your goals?
10. What are your weaknesses?
11. What are your strong points?
How to answer these questions
You need to leave a good impression and show that you can fit in their culture and at the same time show that you meet their requirements. To do this you need first to know the company's vision and culture and focus your answers on what will match this vision. The same goes for the experiences you will need to understand the role requirements and what they are looking for and emphasize the experiences that show these requirements. It will be always better to focus on and highlight the impact before going into the technical details.
2. Questions About The Company & Role
The second type of questions in a data science behavioral interview is questions about the company and the role you are applying to. These questions will focus mainly on your motivation to join the company and this role exactly and to know more about whether you will fit the company culture or not.
Here is a list of famous questions in this category
1. What would make you choose our company over others
2. What do you value most at the company you would like to work in?
3. What are the three things that are most important to you in a job?
4. What do you think you will bring to this position?
How to answer these questions
To be able to answer these questions effectively you will need to do research about the company and know its core values, vision, and what they are looking for in its future employees. Also, you will have to define what exactly your core strength is and how this will help the company.
3. Situational Questions
The last type of question you will see in a data science behavioral interview is situational-based questions. This usually makes up the largest portion of a behavioral interview and it might overlap with the previous two categories.
The main goal of them is to see how you will act in a difficult situation that you will probably face and to know more about you and your personality in a practical way.
Here is a list of famous questions in this category:
1. Tell me about a time you have to work on a strict deadline
2. Suppose you are working with an underperformance teammate, how you will handle the situation
3. Tell me about a time when you disagreed with a supervisor
4. What is the most difficult/ challenging situation you’ve ever had to resolve in the workplace?
5. Tell me about a time when you failed in a team project, and how you overcame it.
How to answer these questions
These questions require you to tell a story, however, if you want to stand out, you have to go beyond telling a story. Make use of every story to show more about yourself and focus on the values of the company you got from your research about the company.
Some of the common attributes to show:
1. Being proactive: Being proactive is a very important attribute in the workplace as it allows you to dictate your position and supplies a sense of control over whatever situation you may be facing. Essentially, your proactivity will enable you to be more prepared. When you are proactive you can think and act ahead before your circumstances change.
2. Passion for your work: You should show that you are excited about what you do and passionate about it as this will leave a good impression on the interviewer. Doing work you are passionate about will make you creative and more productive.
3. Flexibility: Being flexible and able to adapt to short-term changes and unexpected problems quickly and calmly is a very important skill and attribute to show as this gives the impression that you can work on different tasks and adapt to changes in requirements that are expected to happen.
4. Leadership: Leadership skills are important not only for senior positions but for even entry-level positions as it shows your potential if you got promoted and have to lead team members after that.
5. Communication: This is a very important skill for every data scientist as you will be working with people from different backgrounds communicating your ideas and results, so it is important to focus on showing this when you are answering different situational questions.
Finally, it is important to make sure to be prepared before the interview and use specific examples and be concise with your answers. Always tell the truth. Another great tip is to understand the company and have some solutions in mind. Great tech startups are looking for solution-oriented employees who help them increase revenues, decrease costs and save time. If you can prove with your examples and insights that you can do that, you’ll be in high demand!
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