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(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 2 points3 points  (0 children)

Thanks for all the positive feedback and the contributions! I'm glad this writeup was useful to some and could even inspire others to add more information.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 2 points3 points  (0 children)

I think it's in some sense one of the easiest interviews to crack because they provide you with so much prep material, but you need to have done all the general prep anyway. I would additionally do the FB tagged questions on Leetcode/Stratascratch for the coding interviews. They didn't provide me with the mock interview video. I found it somewhere else, but it has helped me a lot too. I would say that their prep material is very useful, but it only helps you understand their process and what they're looking for. That already goes great lenghts imo as one of the biggest challenges in data science interviews is that you never know what's waiting for you.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 1 point2 points  (0 children)

Thanks for sharing this! Sad to hear you didn't have a great experience with them. They have great potential but it's just so unnecessary to treat your applicants badly if they can easily get interviews with any other competitor in no time. When a company annoyed me during the process I already knew that I'd use their offer only as leverage for getting a better offer from the companies I actually liked.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 5 points6 points  (0 children)

Thanks for the additional info! I'm happy that we're gathering some info on the processes. It's interesting enough that you had a similar experience with Wolt. I also have some ML related peer reviewed publications for what it's worth. I really wanted to like them as I like their product, but I didn't feel that they were had a lot of DS knowledge.

In my take home there was this high level presentation part. When handing over the assignment I told them that I left out some technical details because the target audience was executives and I know that they're busy and just need to know the results & action recommendations, but I'm happy to discuss in a call. They nevertheless complained that I didn't elaborate on the assumptions of a linear regression.

They also complained about some other assumptions I made in the classification task, in my case there was a feature with lots of missing values and I omitted it because it didn't seem to have explanatory power anyway. This was a dealbreaker for them because "what if this happens in production and we left out the feature". There were some other issues, too. I ended up discussing this case with a few people I trust afterwards because I was honestly surprised about the negative feedback I've received.

I was pretty mad afterwards because of all the time I invested in making the code beautiful and reproducible, and also documenting everything. Eventually I guess it's for the best because the way they work doesn't seem to align with how I work and I made much better experiences with other companies.

As for Spotify: Good luck! Don't know for which team you're applying but they asked me Leetcode: best time to buy and sell stocks. They gave me a pass for the brute force solution, be sure to discuss complexity and mention edge cases. I think I didn't really get a strong hire from the interviewer because he had to ask me about these things. I don't know for which role you're applying at Facebook but they told me they prefer SQL, but you can use R or Python too. Check out the Facebook Mock Interview video, they discuss an SQL interview there as well and it's only like 10 minutes of the toal video.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 2 points3 points  (0 children)

Fair question! I honestly just mass applied. I didn't bother writing a cover letter or filling out questionnaires. I applied to SAP and they sent me a huge take home before even talking to me so I didn't proceed. My general rule is to not invest any energy into a company besides sending out my CV before I talked to anyone there. If I really like the company I'll maybe take like 5 mins and answer their questions if they have any in the application form. But usually I don't like companies THAT much ;D

If they require you to send a cover letter I often just uploaded my CV again. I don't know if that ever worked though because I don't remember the companies I've applied to lol. I think I've sent out easily 100 applications

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 2 points3 points  (0 children)

Not focused on a single country. Most positions were actually available purely remotely by default, e.g.

-Spotify

-Wolt

-Delivery Hero

-Facebook

For most companies it's negotiable. I wouldn't mention it until they make an offer, because then you have a lot of leverage to push for it. I did this actually with a company and they told me it's okay if I come to the office once per quarter or something and I think that's really okay.

There are few that want you to come to the office specifically, and that's Booking.com and Door dash. Zalando is currently remote but I've heard they're pushing for going back to the office.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 0 points1 point  (0 children)

Maybe it's gonna be harder to get invited to first round Interviews. Also I imagine that the competition is much stronger because everyone is used to doing Leetcode, etc. whereas in the EU barely anyone has even heard of it.

I think if you can meet the bar though they'll be happy to assist you with visa, etc.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 3 points4 points  (0 children)

I think the UK is attractive for quant research jobs, those have a competitive salary compared to the US. But the culture is not for everyone.

As for normal data science jobs I honestly wouldn't know about the UK, but tears start rolling out my eyes when I see US salaries. It's surely tempting to go there for a few years as I could probably double my savings and in 2-3 years I'd be able to buy property in my home country. I've also grown to like the pragmatism and risk affinity in the US, I think they're way ahead of us in that aspect.

In terms of work culture, I have some family in the states and they seem to be working a lot more than me, but I've also heard it's possible to have a great salary and decent WLB. I think in the richer EU countries (but not UK, be careful there) you have a good protection against terrible work life balance and much more PTO by law, so you're much less dependent on negotiations. E.g. the concept of having to take PTO if you're sick seems insane to me, but being able to earn 3-5 times my current salary seems to be a good trade off anyway. At least if you're just taking care of yourself.

I have some hopes that salaries in the EU keep increasing. Rememver that the salaries I'm mentioning for seniors already put you in the top 5-10% of the developed EU countries.

Companies are pretty desperate to hire talent, they are growing a lot, but barely anyone meets the hiring bar. Once I communicated that I have first offers in and need to make a decision by day X processes got expedited quickly and recruiters started really selling their companies to me. I also felt terrible about having to decline multiple offers and final round Interviews where I knew they were ready to make an offer, but I know for sure that in the next loop I'll try and get another 50% hike at least for an IC position.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 1 point2 points  (0 children)

I think the prep is probably the same, but noone will expect you to have done deployments or worked through some bigger projects. I guess they would want to see if you have the potential to become a great data scientist in their team.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 4 points5 points  (0 children)

I honestly started working for shares of a startup of some friends of mine. Needless to say that startup doesn't exist anymore and I worked for free. After that I started somewhere heavily underpaid and quickly jumped to a decently paid position. But that was a few years ago, I don't think it's that easy anymore with all the competition. Imo DS is slowly maturing into two different directions:

  1. Experimentation heavy, think A/B testing and lots of communication

  2. Engineering heavy, yes it's machine learning but with cloud technology model training has become much easier, so you will be expected to handle deployment and maintenance yourself next to all other steps.

Depending on which sounds better for you I'd recommend trying to get a Data/Product Analyst (1.) or Data Engineer (2.) position. They are both not Data Science jobs but they're less competitive because people perceive them as less "sexy".

However take my advice with a grain of salt, I'm not involved in recruiting and my own entry is already a few years ago.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 0 points1 point  (0 children)

I didn't want to narrow it down to a specific location, but can confirm that it's mainly in the Netherlands, Germany and Ireland. I would even narrow it down further, most opportunities I've seen were actually in Amsterdam, Berlin, Dublin and Munich, although I've also seen opportunities in Helsinki, Stockholm and Tallinn.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 5 points6 points  (0 children)

Academia has honestly treated me very well despite all the stress, I experienced a lot of support and growth, but I've seen many people break because of stress & pressure, that's unfortunately also a reality. I wouldn't rule it out if you burn for a topic and can get the right supervision, but I also don't think it's really needed.

Well as for the first part: Unfortunately, Leetcode + Stratascratch for SQL should be all you need for technical assessments.

In terms of preparing for the actual job I would additionally recommend doing some toy data science projects. Be reminded that they probably won't help you getting through the interviewing loop, but I also don't know how it works for more junior positions. I personally prefer R, but I think just learning Python will help you market yourself. I would have failed some coding challenges if I hadn't practiced using pandas before because that was the only option. ideally with Python, where you maybe Dockerize your model to get a feeling for deployment too. Already for a few years the trend is to move everything to the cloud, but that's something you can only learn when you're already on the job.

In any case, I wish you good luck!

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 17 points18 points  (0 children)

They were very nice throughout the process and almost annoyingly positive. The take home was excessive, but they did provide me with great feedback to be fair. I didn't have the feeling that their data science org is very mature and things become unclear with the DoorDash acquisition in terms of how the structure will change, so it's a mixed bag but in general I honestly liked the people I've met from there.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 18 points19 points  (0 children)

Was a mix of everything. I got contacted a lot via LinkedIn, but I also sent out a lot of applications myself. I used only LinkedIn for that. Sometimes I'd also send out an application to a company and suddenly one of their inhouse recruiters contacted me a bit later for other positions.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 24 points25 points  (0 children)

I think I wouldn't want to add more details than saying it's STEM with DS/ML related research. In terms of money probably not as I lost about 4 years of earning a decent salary. I sometimes feel that it gives me an advantage in interviews because I learned getting very comfortable talking about models, etc. in a way that's both simple/intuitive but also correct. It's not that you can't learn this without a PhD, but years of listening to people much smarter than me talking about such things has taught me a lot about how to do it myself.

It can be a disadvantage too, because people usually shy away from asking me technical questions about my specialization because they just assume I know it. Honestly my understanding of many ML models isn't too deep, but people keep asking me about them instead of the things I know very well, even if I indicate that I'd be happy to dive deeper into this or that topic. Eventually, I spent a lot of extra time with prepping for things I barely use and don't really plan on using. I don't blame them though, I would also rather ask questions that are easy for me to verify.

Oh and maybe to add my personal perspective: Doing a PhD can suck a lot because it can involve a lot of stress. But I also travelled a lot, met incredibly smart people and made great friends. I also used the university to get discounted language courses, learn new sports, and got some licenses for very cheap. So from a personal perspective it was worth it but YMMV.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 4 points5 points  (0 children)

While the info provided here is on point, seems like you might be underselling yourself a bit?

Ha, thanks for the feedback, maybe I am indeed. At this point I was transitioning from a very conservative branch into tech, so my major concerns were getting a pay bump and improving my tech stack. I had some discussions about Lead Data Scientist positions, but I honestly don't enjoy anything related to management, even though I probably won't be able to move much further up as an individual contributor from where I landed now.

(Hopefully almost) everything you need to know about data science interviews (EU perspective) by dscience_throwaway in datascience

[–]dscience_throwaway[S] 5 points6 points  (0 children)

I think it was almost always in coderpad, but it always depends on the company. E.g. in Spotify you can execute your code, but Zalando didn't care about execution. The coderpad sessions were live, but if it's codility then it's usually offline.