top of page
Search

OUR HOW TO’S IN NAILING A DATA SCIENCE JOB INTERVIEW



So you’re looking to start a career in data science. You’ve updated your resume, applied to a good handful of jobs, and are now waiting for a response.


Gosh, why is it taking so long for someone to get back to me?


Hitting the nail on the head is easier said than done. With data scientist and AI professionals jobs in increasingly high demand, it is important to know how to stand out in this industry and be prepared the next time a job interview arises.


Luckily for you, we’ve combined all our top tips and shared them below - if there is anything that you think is missing, pop in a comment below or tag us on our LinkedIn page!

1. Determine what area of data science appeals to you:

There is a lot of noise to compete against in the data science industry. One way to quiet the sound is by getting a better understanding of which area of data science most appeals to you.


Start by doing some research on data science to narrow down which particular area of appeals to you most. Look back at your most favourable project, or a subject you studied that you thoroughly enjoyed. As soon as you're able to identify your area of expertise, the sooner you will be able to showcase your abilities in your next job interview.

Ask yourself a few questions in relation to the area that you want to work within:

  • What do I want to learn within this area that the role is in?

  • What can my career path look like if I were to take on this role?

  • How will this role help me achieve my professional goals?

  • What resources do I have around me to help me through this role?

2. Understand your competition and get yourself ahead of the game:

Establishing the fact that data science is a highly competitive industry, you don't want to be 'just another candidate' in the job pile of a potential employer. There are various ways to make your skills and experiences stand out in order to get an interview:


1) Attending data science and AI information days:

Attending these information days will enable you to connect with industry professionals and potentially get a foot in the door. Have your updated resume on hand and ask the industry representative if they would like one. Another tip is to grab a business card of whomever you may be looking to reach out to in the future for potential opportunities. Don’t however, find yourself with a stack of business cards! Network with the right people and have a genuine conversation with them.


Conversation Tips:

  • Don’t self-deprecate or play down yourself.

  • Express your fields / areas of interest.

  • Discuss Any passion projects that you have been a part of.

  • Possibly research the company beforehand and ask following questions - i.e. “I would love to get an understanding of how [COMPANY NAME] supports the career progression of young individuals like myself looking to establish a career path in [AREA OF INTEREST].

  • Don’t find this tacky - most often you may or may not know who is going to be present at the information day. If you do, it won’t hurt to search their LinkedIn profiles prior! This is a tip especially for those who may have difficulty in continuing or carrying a conversation.

  • Connect with these individuals and follow aspiring companies you wish to work for. When adding your connection, add in a note thanking the rep for their hard work and efforts in providing you with insightful information about [XYZ]. Even adding a sneaky, “It would be great if we could catch up for coffee one day to further discuss [XYZ i.e. your journey within the XYZ field].


3) Completing a data science membership program:

These programs are designed to help upcoming graduates get job-ready, certified, and started in the industry. Not only does completing a certification look good on your resume, but is well sought- after and valued by employers.



Useful Links to Check Out - you may even have a society to join within your university!

  1. Data Science and AI Association of Australia: DSAidsai.org.au

  2. Institute of Analytics Professionals of Australia: Homewww.iapa.org.au

  3. Data Science Associationwww.datascienceassn.org

  4. Data Science Society: About Uswww.datasciencesociety.net


3. Understand the technicalities of the job description:

There is no absolute way to know how an interview will play out, but the resource that you do have is the company's job description. It is always best to structure your answers around the job description as a way of demonstrating your understanding of the role, the goals and objectives of the position, duties and responsibilities, and requirements.


Is the interviewer looking for an analyst or a programmer, an engineering specialist or a consultant? What skills are required to succeed in the role? Understanding what the interviewer wants from you and displaying what you can offer to the company will add value to your interview.


Another point is to back what you’re saying with examples. For example, you may have a question thrown at you asking “what’s an example of a situation where you faced a complex problem at work? How did you solve it?” Rather than saying, “well a few years ago” - NO. Avoid ‘fluffing’ around, cut straight to the chase and use the STAR methodology when it comes to behavioural type questions.


In short, the STAR methodology or interview response method, is a great way to help you prepare for all the drilling questions that recruiters may ask you typically behavioural-like questions. Behavioural questions are questions in which you are asked to describe previous work scenarios and are good predictors to the recruiter as to how you will handle a similar situation in the company that you are currently being interviewed for.


If you don’t know what the STAR method is, you can check it out here (kudos to Indeed for their excellent interviewing guides).


The STAR method helps you create an easy-to-follow story with a clear conflict and resolution.


Here’s what each part of the technique means - thank you again to Indeed who breaks the methodology for us in easy steps down below:


Situation

Set the stage for the story by sharing context around the situation or challenge you faced. Share any relevant details.


For example, “In my last role as lead designer, my team was short-staffed and facing a significant backlog of work. The account managers were setting unrealistic deadlines, which was causing stress for my team and affecting morale.”


Task

Describe your responsibility or role in the situation or challenge.


For example, “As a team leader, it was my role to not only ensure my team met our deadlines, but also to communicate bandwidth to other departments and keep my team motivated.”


Action

Explain how you handled the situation or overcame the challenge. If the action was carried out by a team, focus on your efforts.


For example, “I set up a formal creative request process including project timeline estimates to set better expectations. I scheduled weekly meetings with account managers to discuss my team’s bandwidth and share progress updates.”


Result

What was the outcome you reached through your actions? If possible, quantify your success or provide concrete examples of the effects of your efforts.


For example, “By providing more transparency into my team’s processes and setting better expectations with the account managers, we were able to re-prioritise the design team’s to-do list and complete everything in our backlog. The following quarter, we shortened our average project timeline by two days.”


4. Be prepared to talk about your recent projects:

The interviewer will want to know how you have utilised your skills in a project environment.