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How to interview the company that is interviewing you for data jobs

A guideline for making use of the last 5 min in your interview

Photo by Sigmund on Unsplash
Photo by Sigmund on Unsplash

1. Background – interviews are not a one-direction choice

Starting a new job can be exciting and scary at the same time. In my previous blog, I talked about a 4-step method to talk about your projects in an interview. For many people looking for a new role, starting the new role can feel like buying a ‘mystery box’ – you would not know what’s inside before you open the box. Especially for data jobs like data scientists, data engineering, and data analysts, "a typical workday" could vary quite a lot – for roles in the same industry or even in the same company. Even if you have the same title, the tools you use, the skills required, and the kind of data used for projects vary depending on the team. Therefore, understanding what you would need and what your work would be is critical.

I doubt anyone would love to be surprised to see the new job is far from what they thought it would be, especially in an undesired way. Many people prepare hard to show their best in the interviews to impress the company, but many less experienced candidates usually omit a thing: Evaluate and interview the companies, not just let the companies evaluate you.

2. When?

Now that we know that we want to understand more about the role during the interviews, the next question would be when we could conduct our interview of the company? Usually, in the interview, the last 5–10 minutes are for the interviewees to ask questions to the interviewers. It is great to get the answers we need about the new job. If you think this time is not enough or did not have a chance to go through this step, I suggest you bring it up and ask for some time to do your part of the interview.

3. Who?

Most people probably think the future manager would be the best one to ask questions, but I don’t suggest you have limitations like this when thinking about interviewing the people. Everyone has his role and perspectives, while everyone can be biased due to where he’s standing. Therefore, you should learn what questions to ask based on the interviewee’s role. Before we talk about what good questions are, let’s first understand how your interviewers’ roles can determine the content of your questions:

Image by Author
Image by Author

HR

The HR screening is usually the first interview for most data jobs. The conversation is usually about general questions like your current work status, visa status, motivation to change jobs, the interview process, etc. I recommend you ask more detailed questions about the interview process, rather than company culture. I am not saying that you should not "interview" HR, I mean asking HR about company culture is less helpful than figuring out what kind of interviews you would have and how to prepare for them since the time is limited with HR in the conversation.

Future manager

It would be hard to have a successful career without support from a good manager. However, in some interviews(new grad hires or general hires) you may not get a chance to talk to your future manager – the fact is you may not know who will be your manager during this interview.

For the direct-hire process, the manager may be the most important one to determine your offer. And he/she is the one who helps you the most to grow in your new role. So, during the interview, he/she is a good resource to understand the big scope of the team, and the expectations of your work. You need to make sure that you are fine with his management style to work with in the future.

Future coworkers

Colleagues in the same team are probably the people you have the most interaction with during work. They usually have been in the team for a while and are familiar with how the team works and what a typical day looks like for your new role. What you would want to know from them is the atmosphere of the team and culture.

Future business partners

They usually would talk with you during the "panel interview" part. Their roles could be your LOB partners (line of business), internal clients, product managers, project managers, etc. They are someone whose work is impacted by yours, but they are not necessarily on the same team as you or know much about data/ML. Since they rely on your work to do their job, they would have expectations of your performance.

Other interviewers

It’s not uncommon to have interviewers who you will barely or never work with again in your new job. These people can be other employees not on your team, manager from another sister team, or the department head. Though both of you know that you won’t have many interactions in the future, I still think they are good resources to learn more about the department or the company itself.

In summary, I encourage you to ask valuable questions to everyone interviewing you, whether your future boss, coworker, business partner, or just someone who’s in another team and would never work with you in your new job.

4. How?

The next important thing to discuss is what questions are good to ask. While everyone may weigh things differently in a job, I would suggest evaluating the job from the following perspectives:

Image by Author
Image by Author

4.1 Technical requirements

As mentioned above, the actual work can be very different depending on the roles. Here are some questions you may want to ask if the interviewers don’t mention them during the interviews:

  • What are the biggest challenges of this role?

Ask whom? Ask both future managers and coworkers, since they may provide different perspectives. You could also ask future business partners. What do we want to learn by asking this question? For the manager, the answer would indicate his/her expectations of your work – the areas he or she needs the employees to address well. For future coworkers, their answers represent the potential pain points of the job, from which you could predict what may make you pull hair. For example, if their answer is "get clean data for ML models". Then you know that great data cleaning skills are necessary for this job.

If this job requires you to work closely with business partners, you may ask them this question. Similar to the managers, they would set expectations for someone they will cooperate with often.

  • What are the common tools to use? More specifically, what programming language (eg. Python R, SAS). What cloud service do they use(eg. Google cloud or AWS)? What kind of databases/data lake (eg. SnowFlake, Qubole)?

Ask whom? Future coworkers. If you could not get answers from future coworkers, you could ask future manger too. What do we want to learn by asking these questions? The job descriptions usually list the skill set of their ideal candidates. But sometimes the descriptions are either too general or list 100 skills. It never hurts to confirm the skills required, and it’s critical to know if your current skill set can meet them. Additionally, asking this question could help you figure out what’s missing so you could start improving on day 1 of the new job.

4.2 Work routine

You want to make sure that you will like the work pace in your new job, so you will get an idea of what day-to-day life looks like. Here are some good questions to ask:

  • How many interactions are with people in this work?

Ask whom? Future manager, coworkers, and business partners. What do we want to learn by asking this question? Data jobs require frequent interactions with others. Some roles may require a lot of meetings with different people like clients, business partners, and coworkers, so you only have limited time to focus on developing ML models or data products. In some roles, you may cooperate with technical people from different backgrounds (eg. Data Scientists work with Data Engineers), other roles require working a lot with non-technical people to provide business insights or data products. It’s also possible you work solo and only report to your manager. Asking this question can help you understand your daily/weekly routine and see if you would like that work style. When the interviewer is a future coworker, you could also ask a related question like "what does a typical day look like?"

  • How is the work-life balance there?

Ask whom? Future coworkers and other employees that are not on your team. What do we want to learn by asking this question? No matter whether you prefer to keep busy, or want some time to enjoy life, you should always ask this question. And it is a better question than asking something such as "how often do we need to work after hours."

4.3 Administrative information

Many people omit it but it’s important. The world is changing every day. Do not expect to stay forever where you are even if you are the best employee on the team. Company reorganizations, change of leadership, adjustment of policy…any of these can impact greatly on an individual employee. Stay alert and be prepared, even before stepping your foot into the company.

  • What does the team structure look like?

Ask whom? Future manager and coworkers. What do we want to learn by asking this question? Is this team newly established and you will be the very first data scientist there? Is this team expanding because more funding is coming in with many exciting new projects? Or the team is hiring because a few people have left recently? Yes, the structure of the team matters, and you can imagine that it is very different to work in a new team versus in a well-established team.

You may also want to know about other people on this team. For example, for a mid-level data scientist role, I suggest you ask if there are other DS in the team. Any data engineers who do the pipeline work for data models? Is it a Data Science team where everyone has a technical background, or you will be the only DS supporting all other non-technical staff in the team?

Why these questions? I think they highly relate to your career goals. When I was a junior employee, I wanted to work in a team with senior DS that I could learn from. And I wanted to work in a well-established team where people have experience and know the best way to do things. Everyone has different career goals, so make sure the new job can suit what you are looking for.

  • Where is the team sitting in the company?

Ask whom? Future manager, possibly coworkers and business partners. What do we want to learn by asking this question? We ask this question to see if the team is a "cost center" or a "profit center". A cost center, also called a revenue center, is a group or department within a company that performs functions helpful to business operations but does not generate revenue directly. A profit center is a division or department of a company that generates revenue and profits directly [1].

Data-related roles could sit in either the cost center or the revenue center. Some companies rely on ML or other data products to generate profits in various ways, so the teams that create these products are the core of these companies. Also, some companies establish their AI or ML departments to support their core business. In other words, these companies have traditional ways to run their business, and ML is something nice, but not essential. I am not discouraging you to work in a cost center, but I think there’s a higher risk of working in a cost center than in a profit center if you want to reduce the chance of getting layoff for some unpredictable situations.

4.4 Self-development

  • What growth opportunities does the company provide?

Ask whom? Future manager and coworkers. What do we want to learn by asking this question? I think it’s important to understand future growth opportunities when evaluating the job. A job is not just trading work for money; it is also about accumulating experiences and growth. Especially since data jobs require lifetime study, it’s unlikely that we will be using the same tools and technologies in work after 30 years from now. I suggest you ask if the team or the company offers access to online learning platforms such as LinkedIn learning or DataCamp and if they encourage employees to attend workshops and conferences. If you plan to get another degree, you may also want to ask if they have tuition assistance.

5. Please try to avoid asking these questions

  • Questions about money and benefits.

No matter how eager you want to know about the salary, do not discuss it during the Interview, especially with the future manager. You may discuss it during the HR screening or discuss it with the manager only after getting the job offer.

  • Did I screw up in the interview?

I understand you may feel bad when you think you did not show your best, but try not to ask this question in the last 5 minutes of your interview. The interviewers have their judgments, you may think you screwed up, but maybe you did better than other candidates. Or the interviewers asked you challenging questions to test how you handle high pressure. Don’t show that you are not confident in getting the job, NEVER!

Summary – it’s about you, too!

Finding your next dream job is never a piece of cake for most people. Please keep in mind that a job is a two-way choice, not just about the company finding what it needs, but also about finding somewhere you are happy to work, learn, grow, and be a better version of yourself!

Thank you for reading, I hope this blog helps you a bit in your data job hunting, and here’s another blog about data interviews you might be interested in. I hope you will land a great offer. Good luck!

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This blog was originally published on my personal website.

Reference [1]https://www.indeed.com/career-advice/career-development/profit-center-vs-cost-center


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