In my previous article, I talked about red flags you should look out for during a Data Science interview. In this article, I will discuss green flags to look out for in an interview and during the first few weeks at your new job. I should note, as with the previous article, that this is my personal experience, however, I hope that you still take away some useful insights.
During the interview
- You should be given a clear and precise project description during the initial call. Project descriptions are particularly important when interviewing for start-ups, given that big companies will likely have established projects and routines in place already. However, you should still receive a description of what a potential project would look like (e.g. a previous project).
- You should find the project interesting and, most importantly, you should be interested in working on it. It should not involve a significant amount of data acquisition and cleaning.
- You find the coding challenge to be a mix of coding assessment and problem-solving – this should be a problem the company is currently tackling. You should be “assessed” by giving your theoretical insights on how you would solve the problem. For example, the assessment for my previous job (the best job I’ve had, so far) included several multiple-choice programming and data-structure questions, a coding question, two theoretical questions about two projects the start-up was currently working on, and one NLP coding question (given they were recruiting an NLP Data Scientist).
- The final interview should be an interesting discussion about the things you wrote during your assessment. There you will see whether you and your potential line manager or team member will get along and be able to work together.
Note that points 3 and 4 could happen at the same time during a real-time assessment.
When you start your job – how to tell if you made the right choice
- You start coding/contributing from day 1. It will depend on several factors, whether you will be able to commit code within the first few days, such as team size, the pre-existing code base and access to outside data sources. The project the company is working on, should be presented in a way that makes you feel confident and leaves you knowing what to do. If after the first week you still have no clue what to do, or how to contribute, then something is wrong..
- You get all the necessary tools you need to work efficiently. This may be hardware, access to the cloud, access to data, or a certain set-up you feel comfortable with (e.g. jupyter notebooks in a cloud environment with GPU access). This again depends on the established routines within the company/team, and I am speaking from a research-oriented start-up experience here (where I had a lot of freedom). However, if you are required to use a certain infrastructure, you should be properly onboarded and given the necessary training.
- You enjoy what you do. You are having fun, you feel satisfied, and you are contributing in addition to learning something new. This may sound obvious, but you’d be surprised how often people do not feel those things at work.
For example, in my previous job, my first deliverable was due by the end of my first week. It involved topic modelling, which I had not previously done (but knew the theory), so I learned during the process (practically). I felt supported throughout because my boss set everything up I needed to enable me to work efficiently, and I clicked with my boss in general.
Advice if something feels wrong
If you feel like you might have made the wrong choice and the job is not what you expected – for example you don’t click with the team, or you don’t feel happy for any other reason – LEAVE.
It is not worth it. It is better to do it sooner rather than later. Yes – it is just like a toxic relationship.
AUTHOR: Lisa A Chalaguine – SheCanCode Blog Squad
To find out more about Lisa please click here.
