How to Prepare for your Data Scientist Job Interview
Data science jobs are no doubt in vogue right now, as the burgeoning field continues to evolve in its pursuit of utilising data analysis to inform important business decisions. For candidates wanting to break into a career in data science, we shed some light on how best to prepare for your job interview and what hiring managers are looking for.
First thing to know is what specific data science role you’re applying for. Under the heading of data science comes titles such as, Product Analyst, Data Engineer, NLP Researcher, Machine Learning Engineer and so on. Are you more statistics-driven or perhaps a programming whiz? Data science is essentially more of a business function that exists within other roles, so understand where your skills and interests lie at the start of your job search; target companies and jobs you’re passionate about and/or you think you are well suited to.
The greatest advice is to expect anything! You could get questions around coding, why you should use a foreign key constraint, how you’d explain the different between PL/SQL and SQL to your Dad or even how you’d go about heading up a group roundtable discussion about a challenge the business is currently facing.
It’s a good rule of thumb to approach your data science job interview through a technical lens. Even if a lot of the questions don’t sound technical you need to use every opportunity to weave examples of your technical acumen and analytical expertise into your answers. Questions about how you’d navigate a certain business problem are a subtle invitation to expose your strength in analytical problem solving and your subsequent ability to convey your technical solution to non-technical business leaders and stakeholders.
You’ll likely be tossed a few open-ended questions that present you with broad, real-world business problems or case studies. These are designed to gauge your USP among the many data scientist hopefuls competing for the same role. You have the chance to reveal a 360 view of yourself in how you relate to a problem, what your goal is in solving it and how that directly impacts the business or industry you’re working for. Show your thought process and ability to weigh up the pros and cons of various possible solutions so your interviewer really gets a sense of how you operate, both individually and ultimately as part of the team.
Don’t be afraid to ask questions yourself. Draw your interviewer(s) into the discussion if you need some clarification on certain things, at worst this demonstrates just how well you do work with others and aren’t afraid of seeking your colleagues’ input. Arrogance will get you nowhere.
Regardless the type of data science role you’re interviewing for there is a good chance you’ll be asked about projects you’ve worked on. The way you answer tells your interviewer the following things:
- How well you can translate your technical thought processes into everyday language
- Your ability to collaborate within a team
- Your awareness of the potential ethical implications of your work
- Your passion for working in data science
It’s best to have some examples ready to go ahead of the interview, so think about the algorithms you used, list all the models you tried and think about the analysis you did throughout the projects you’re planning to talk about at the interview. Did you start simple with straightforward models or did you get busy with more complex options straight off the bat? Decisions like this are very revealing about how you work so think carefully about how you’re presenting yourself.
Questions around logistic regression, neural networks, the CART algorithm and so on may also appear and you should be able to show that technical understanding, but ultimately the hiring manager wants to hear about your past project experience, so it’s in relating those technical elements to that experience that will make you shine.
Be honest when faced with questions outside your experience, know your own CV and project history like the back of your hand and be ready with talking points about the job you’re applying for, what you’ll bring to the role, what you’re looking forward to working on in the new role and any ideas you may have that could help innovate current processes and in turn impress your future employer.