In this article, we will get to know the flow of a culture fit interview for a Data Science job and some pointers on how you could answer the questions asked.
A culture fit interview is to determine if you share your values with the company and how compatible you are with the way the company works. This takes place after the technical round. When you have the required skills to fill the position and you have a top notch resume, the final step (mostly) before hiring you is the culture fit interview. It approximately lasts for half an hour where the interviewer tries to understand you better - the values that you stand by , your vision, goals, and passion so that the company is sure that they are hiring the right person for the role. The questions asked here will be personal, situational, and behavioral and nothing technical!
Interviewer : Introduction
The first question in any interview goes like "Please introduce yourself" or "Tell us about yourself". This is the basic interview question where the interviewee is required to introduce oneself. Since this will be your first interaction with your interviewer, make sure that you get off with a good start. As they say, first impression is the best impression!
Start by briefly sharing your background and experience. This is where you tell the interviewer who you are. Structure it around your professional life - discuss your education, skill and experiences you gained relevant to the position and your capabilities. Go a step further and make sure your answer connects with the company's vision and mission. Also explain why you are interested in the position that you have applied for and why would you be a good fit for the same.
Interviewer : What do you think makes a good Data Scientist?
Now, this question is not exclusively for the role of a data scientist but can be asked for any position that you have applied for. With your answer for this question, the interviewer will get a sense of your views on the role and an idea of what values you bring in if hired.
For a Data Science based role, you could talk about the expertise needed along with all the relevant skills that are required to do justice to the role. You could state the willingness and passion needed to constantly learn new things and you can also talk about your favorite data scientist - be it a peer or a famous data scientist and why you look up to them.
Interviewer : Why do you want to be a Data Scientist?
Again, this too is a general question and not specific to just Data Science. You can start by saying that you are passionate about working with data. Then you can go on to elaborate what inspired you to take up this field - this can be the challenging dynamic of the field, your passion for problem solving or the joy you feel when you turn meaningless numbers into something meaningful.
Additionally, you can talk about some emerging technologies relevant to the field that excites you. The interviewer will appreciate your knowledge on the technological advancements and this might give you an edge.
Interviewer : Where do you see yourself in five years?
This is a very common question which gives the interviewer an idea about your career goals and how do they align with the company. This will also help the interviewer know whether you will be a long term or short term employee.
For answering this question, you must be clear about your career goals. Of course life can be unpredictable, but having a basic plan never harms. Be sure to link your career goals with that of the company if you are sure that the company will help you grow as a professional. If not sure, you might want to reconsider your application.
Interviewer : What are your strengths and weaknesses?
When the interviewer asks about your strengths and weaknesses, start with your weakness first so that you could end on a positive note. While discussing your answer, make sure that you state the traits that are relevant for the job. Additionally, add an anecdote as to how this trait emerged in your life. This shows the interviewer the level of your self-awareness. While stating your strengths, ensure that you strike a balance between humility and projecting your confidence.
Interviewer : How do you measure success?
Now this question doesn't have a right or wrong answer. This question is asked so that the interviewer could get a sense of your work ethics. The best way to answer this question is by quoting your past successes. Explain about the element that were a part of your journey to success. Proceed on to share what you learned from each experience and how you implemented them in your life. Lastly, do not forget to give credits to your team members if it was a team effort.
Interviewer : What are your hobbies outside of Data Science?
Some interviewers do ask about your hobbies to know if you spend your free time wisely. Pick out your extra curricular activities carefully before you state them. Attach a value that you learn from them like team work, leadership skills, etc. And finally make sure that the extra curriculars and values you mention are somehow useful for you in the professional front.
Interviewer : Do you prefer to work alone or as a part of a team?
When you are asked this question, start by stating what you feel are the advantages and disadvantages of each case as there are both pros and cons of working in a team and independently. Next, state your preference and explain why you prefer working in that setup. For example, if you are motivated to do work all day when you do it independently or if working in a team gives you the push you need, tell the interviewer the same. Use your past experiences to back your preference. And finally, ensure that you discuss how open and flexible you are to work in both environments to make sure that your point is understood and that you don't seem too closed off to new changes.
Interviewer : Recollect a project that you have worked on where you encountered a problem or challenge. What was the situation, obstacle and how did you overcome it?
Before you answer this question, consider the challenges you have faced previously and discuss the one that suits the description of the role you have applied for. First, give an overview of the context to your interviewer in a brief manner so that he/she is able to visualize the challenge. Tell the role that you and others involved played in the project and proceed to explain the actions you took to overcome the challenge. If possible, quantify your results and ensure that you are honest and end in a positive note.
Interviewer : What is your approach for managing and meeting tight deadlines?
Be realistic while answering this question as the answer determines how well you work under pressure. Quote anecdotes from past experiences and tell them how you met tight deadlines and walk them through the process.
For example, if you have to meet a tight deadline for an analytics project, you can start by emphasizing the point that you won't agree to deadlines that you can't meet. Tell them that you divide the project into different parts and come up with smaller tasks like removing outliers, extracting important features and creating various visualizations leading up to the bigger ones like cleaning data, finding a pattern and deriving insights. This presents the point that you are organized even under tight schedules and move one step at a time.
Interviewer : Talk about a situation where you met your goal and how you achieved it.
The interviewer is more interested in how you achieved your goal rather than what it was as an answer to this question. Briefly discuss your goal, why did you choose it, what was your plan of action and what necessary steps you took to achieve the goal. The example that you give must convey your determination and commitment towards achieving your goal. And the goal you choose to quote may be a professional or an unprofessional one.
Interviewer : Talk about a situation where you failed to meet a goal and what went wrong?
Interviewers ask this question as they want to know how you handle setbacks. So don't squirm uncomfortably and get to the part where you handled failures quickly. First, define failure in the context in your own words like " Failure for me is not meeting my own and others' expectations". Make sure to pick a real failure. Don't quote anecdotes like getting a C in a test. Then proceed to share the lesson you learned - talk about what you think went wrong, what would you do differently if you had another chance and how you plan to implement the lesson learned in your life.
Interviewer : Tell me about a time when you had to work with someone difficult to get along with. How did you handle interactions with that person?
This question is asked to assess your ability as a team player and your personality. Start by giving an overview of the situation. While telling them, do not let your emotions play and portray the situation in an objective manner. Instead of how you felt about your co-worker, tell them how he/she affected the project or team. Reflect on your actions and consider what you could've done to avoid the conflict. Then proceed to tell them how you dealt with the colleague and mended your relationship with him/her. Speaking objectively is the key here as it tells the interviewer that you are capable of resolving professional differences without being emotionally invested.
Interviewer : How do you resolve a workplace conflict?
Answer this question very carefully as it determines how you value your workplace relations. Some points to include here are: talk in a private place, make sure all the involved parties are understood and are heard, investigate the situation and find the root cause of the issue, find common ground and agree on the best possible solution. Last but not the least, find ways to prevent such conflicts in the future.
Interviewer : How do you build professional relationships with your colleagues?
Start by defining a good professional relationship - one that has trust, mutual respect, good communication and inclusion. Then tell them the work you put into building your professional relationships. Some valuable points to include here are scheduling time to socialize and develop relationships, appreciating your colleague's work, being present whether it may be team outings or meetings, being committed, being a good listener and offering assistance and when to ask for one.
Interviewer : When talking to a colleague or client from a non-technical background, how do you explain complex technical problems or challenges?
Making non-technical audience understand technical challenges and complexities determines the extent of our knowledge on the particular topic. Although this is totally up to you to express your style of communication, some valuable points to quote are: using humor, storytelling methods, visual aids and avoiding usage of many technical jargons. Again, any supporting real life anecdote would be an icing on the cake! Throughout the answer, the interviewer must get the point that you listen to your audience and focus on the impact that you can have on them.
Interviewer : What are your thoughts about working in a multi-disciplinary team?
Your answer to this question must emphasize the fact that you are a team player. It is common for an analyst / data scientist to collaborate with product developers, financial team, software developers, marketing teams, sales teams and high-level executives. Quote situations that tell that you can communicate and work with anyone comfortably. You can also add in points like how working with different professionals could be a great learning experience for you and an opportunity to get to know them and expand your network.
Interviewer : Can you think of a professional situation where you had the opportunity to demonstrate leadership?
Interviewers ask this question to get an idea of how you can contribute towards the company. First, define your own interpretation of leadership and make sure it's authentic. Then, follow the STAR method to structure your answer. STAR stands for Situation, Task, Action and Result. Structure your compelling anecdote in this way and you'll be a strong candidate for the position.
Interviewer : What is your approach in handling sensitive information when required?
Interviewers ask this question to assess your trustworthiness, loyalty and also to set expectations of your work ethics. Start answering this question by telling them the categories of confidential information that you may encounter and the role they play in your job. Then you may tell them your strategies to deal with such information. As a data analyst, you may encounter customer data, confidential company data and many more. You can share your approach to protect the data - by protecting them with strong passwords, destroying copies of data when they are no longer in use, using secure, encrypted platforms to access them. Use general examples of such cases in your field and also describe the results of your actions. When quoting personal anecdotes, make sure that you don't sell out the confidential information too!