8 takeaways from Data Science interviews

It’s been a while since I’ve shared an article, so hello again!

Disclaimer: This article was written in August 2021, the principles still hold however some of the sites and features mentioned may have changed!

I’m excited to write more articles in 2024 and share my journey as I move from Data Science to Data Engineering!

Applying for jobs can be a time-consuming process, in this article, I’ve pulled together some things that I’ve learned during my recent job application process.

I was interviewing for several roles during this time, each had several stages of interviews — the interview structure varied for each role but they all started with an informal chat with the internal recruiter to find out more about the role, the company and whether it would be a suitable fit.

Following from there, I experienced a combination of — interviews to talk through my experience, take-home tests, presentation of take-home test findings, technical interviews (SQL, quantitative analysis, statistics, data structure, algorithms), case study questions, and behavioural interviews.

Personally, I am not a fan of take-home tests, especially when applying for several jobs. I do enjoy a data challenge however when you are exhausted from a pandemic, your day job and also preparing for other stages of other job applications, I would much prefer to be assessed in an interview setting!

Here are my top takeaways from my recent job hunting!

1. Find a CV buddy

Updating my CV can sometimes delay me when applying for jobs as it’s such a daunting task, I tend to put it off. On top of that, I often find myself getting stuck when trying to recall projects I’ve worked on and highlighting relevant details for the role I’m applying for — I’m too much of a perfectionist.

This time, however, I found myself a CV buddy — a friend who was also looking to update their CV. Over several video calls, we took turns going through our CVs, providing feedback to each other and the process of talking out loud helped to clarify important details. It certainly helped that they were also looking for Data roles so knew the types of skills and experience that would be applicable, but the most valuable part of teaming up was when explaining what we did in each role and having the other person summarise and pull out the relevant points! By discussing my work and being prompted by questions, I was reminded of substantially more details and was able to reword sections more succinctly. It was an iterative process over a few weeks where we would take our notes away, work to improve and come back together to further refine and we both came away with CVs that we were proud of.

2. Start with shared resources

In a few of the application processes, the recruiter provided links to resources that would be helpful when preparing for the interview. I briefly looked through these and spent time on the ones I considered most relevant, however in one case, I left a 1.5 hour YouTube video until later in the preparation as it felt overwhelming how long it was alongside many other resources that had been sent and I had collected myself. When I eventually got around to watching it, the content was incredibly useful and I regretted not watching it sooner!

3. Research the company and job interview process

It is also worth checking out Glassdoor as many people share their interview experience and the types of questions that they were asked in the interview. I made note of many of these questions to make sure that I was able to answer them, and also these came in handy when practising answering questions out loud. There are also many articles on Medium where people have shared their preparation for Data Science interviews, or with specific companies. My list of resources that I wanted to work through was way longer than the time I had to prepare so required some prioritisation. As mentioned above, in hindsight I should have started with the resources shared by the recruiter but I spent more time on the more technical-focused articles and tutorials to ensure I was up to scratch with those skills which, due to the level of detail and understanding required, was very time intensive!

4. Break it down

If, like me, you are preparing for several interviews in parallel, it can be useful to break down the interviews by topic, time required and memory retention. For example, if you have two interviews, both of which will be assessing your coding skills and a case study and one of them also has a behavioural interview, then it may be worth leaving the behavioural practice until last since you may wish to prepare some situations as examples that may come up. I find these types of questions are best to practice a day or two before the interview so that they are fresh in your memory.

For the coding, this is likely to be building on skills you already have and can be broken down to practising a few questions or running through a section of a tutorial each day leading up to the interview. If there is an area that you feel particularly weak in then it is useful to spend more time on this early on and you can then continue to practice questions on this topic to ensure you are confident and able to apply it — again speaking from experience here, I have little experience using SQL window functions and dedicated a fair amount of time to learn and practice these initially so that I felt confident in my first interview however before subsequent SQL interviews I didn’t spend much time practising these and panicked when under pressure. Before a final SQL interview, I knew that this had tripped me up previously so again spent some time practicing but by then I had lost my confidence and having only a day to prepare I didn’t feel as ready as I did in my initial interview!

The case study, for me, was quite a new concept in an interview so required some reading to understand what may be asked and how best to prepare. Personally, speaking through a scenario out loud with someone where they asked follow-up questions was the most helpful method.

5. Find out more

Throughout the recruitment process, I was able to talk to people within the company to ask questions about working for the company and was even offered a chat with someone about interview preparation. I’m not sure if this is usual as I’ve never come across it before but running through a practice interview question and being told what the interviewers would be looking for was incredibly helpful! After having several interviews though, each one was good preparation for the next since the types of questions and interview techniques were similar.

Another good tip would be to use your network, whether getting in touch with a connection who works for the company already or you could ask people you know who have recently got new jobs about their experience with recent interviews — there will be similarities in many of the interview processes within different companies for Data roles so it’s worth finding out more about what it was like for them and any tips they may have.

6. Interview practice questions

Here are a few resources I found useful when preparing for different types of interviews:

Statistics

Brilliant has a wide range of statistics and maths courses, I really enjoyed the style of the questions however some courses do have overlapping content so it is worth being selective about which sections you complete so as not to waste time. I also signed up for the 7-day free trial which was useful for accessing more content but did require a commitment to focusing on stats for those 7 days.

SQL

Mode has an interactive tutorial with access to a SQL database that you can use to practice queries.

Case Studies

Overlapping with SQL, Mode has a few case study examples that are worth working through and also includes potential solutions to compare your answer to.

General Questions

Interview query the blogs contained some useful example SQL, stats and case study questions to run through. I did also try to complete some of the questions on the site however you are limited to running 1 SQL query and viewing only a few solutions, even when signing up for an account so in my opinion the blogs would be more worthwhile.

Medium is full of interview preparation articles for Data Science jobs! Many articles with example questions and topics may come up, I found the articles useful to practice questions however they could often contain too much detail for example, one article contained a long list of Data Science and ML concepts and links to resources, which can be incredibly useful for your understanding but it is unlikely that you will need to learn all of these concepts for an interview.

Be realistic with the preparation time, the foundation of knowledge you already have and what you want from your next role!

7. Practice

As when writing your CV, it can be helpful to work together when preparing for job interviews. If your buddy is applying for a similar type of role, why not practice some of the technical questions together — perhaps choose a topic and ask each other interview-style questions or run through a case study and each prepare your answers — you’d be surprised how much you could learn from each other!

If your buddy is not in a similar industry, it can still be helpful to work through behavioural questions together or find a list of relevant interview questions and get someone to ask you them so that you can practice working through them out loud, communicating your answers (for example, using the STAR method)!

It is also great to have your job-hunting buddies for support when you have interviews, sharing how it went and cheering each other on! I have loved hearing about my friends smashing interviews and finding new roles where they can learn and grow!

8. Growth mindset

Regardless of the outcome of the interview, the time that you have spent researching and learning is helping you to grow! You may not find a suitable role this time but taking the time to reflect on your interview experience, what you have learnt, and requesting feedback from the interviewers will ultimately help you on the path to landing your next role!

Reflections

Whilst interviewing was an intense and busy process, I enjoyed dedicating time to brushing up on concepts that I haven’t used in a while and feel like I am a better Data Scientist because of it. I am grateful that I was offered and have accepted a new role and throughout the applications, I had a clear idea of my goals and expectations for my next role. During this time, I have also been able to reflect on what I have learnt from my current role and habits or projects I’d like to build going forward!

Have you recently been job hunting? What are your top takeaways?

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8 takeaways from Data Science interviews was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.