We all know the feeling of being questioned in a Data Scientist interview. We are even familiar with the kind of questions we are asked, they are specific, general and even open ended.
Just because we completely focus on preparing ourselves for ‘answering questions’, we forget the most crucial bit of the process. And it is asking questions ourselves.
By the end when the interviewer asks us, ‘Do you have any questions?’, we tend to fumble and end up asking questions that make no sense in the context of the interview. Note that, the questions you ask are also a make or break point and it will help you thoroughly impress your interviewer.
So today, you will explore the kinds of questions you can and should ask and what can you expect as a possible answer. Let’s begin.
1. Understanding daily operations
What one does as a Data Scientist on a day to day basis is very important to know about. You need to understand what your day to day tasks will be if you get selected. Make sure to verify this during the interview.
Questions you can ask:
Could you walk me through the day to day of a Data Scientist at your company?
-You should expect the exciting bits as well as the tedious parts. This will help give you an idea of what the expectations will be.
What is the usual time for each project at your company?
-Here you get the sense of work speed.
How many Data Scientists are involved in 1 project?
-This question will help you check how the Data Science team functions.
What is the current size of the whole team? Will it grow in the next 3 years?
-This is to check how important the Data Science team is for the future projects and how much workload you will have to handle.
You may not get the desired answers for some of the questions and that is alright. At least you tried!
2. Past, Current & Future Projects
This is another essential subject you need to ask questions about as it will help you understand the kind of projects you will be involved in. You will get an idea of 2 types of projects which are Business function and Value creation.
It will be easier for you to decide whether you like the projects, fit in the projects or not and how you can expand your skills to be of utmost importance.
Value creation will include verticals like Cost-saving, Revenue generation and Innovative solutions.
Business function will include verticals such as Sales and Marketing, Supply chains, Risk and Operation.
Questions you can ask:
Could you explain the kind of project(s) the Data Science team is dealing with mostly? Is it on the basis of Value creation or Business function?
-You may get a clear understanding of the ongoing projects.
What will be the projects that are assigned to me if I get selected?
-You can expect what is coming your way and be prepared beforehand.
3. Evaluating Performance
Right after you have understood the nitty gritties of the workplace, you should get to know about the performance evaluation process. You have to understand how your manager will evaluate your performance at the beginning.
If your manager is concerned more about the result rather than your effort, you would at least know about this from the start. Therefore your performance review will not be a shock factor by the end of the year.
Questions you can ask:
How do you evaluate performance for a Data Scientist?
-Even though this is a basic question, you will get a clear idea of the parameters for evaluation.
Are KPI’s (Key Performance Indicators) more important or efforts for a performance evaluation?
-This is important to check what is critical as a deliverable.
What kind of KPI’s are usually monitored?
-This makes it easier to know the target KPI’s for the future.
4. Advancing in Data Science
You do not want to be labelled as a ‘job hopper’ if you are switching roles often. You will get the sense of working as a Data Scientist only after you have worked for 1 year.
Therefore you would like to have a secure job that is peaceful enough to keep continuing. The only way to know this is if you ask certain questions at the interview itself. No one knows the future, but you can prepare for it.
Questions you can ask:
How do you plan to grow the team of Data Scientists?
-This will give you a clear idea of the number of resources a company aims for. It reflects the future direction as well.
What does the team look like 5 years from now?
-This is to check whether the team is only a support unit or a product/business partner.
PinHow many members are there in the team currently?
-If you sense there is a margin, there is room for you to grow vertically in the organisation.
As final thoughts, it is always better to have a set of questions prepared beforehand. You may take out the notebook at the end of the interview and ask these questions for your benefit.
We hope these 13 questions will help you crack a Data Scientist role at your dream company. Make sure to check out similar blogs here.
