WHY ARE DATA ANALYST INTERVIEWS LIKE THIS

[u/Nearby-Cockroach8655]

I’m currently interviewing for data analyst roles (mostly entry level) and every take home task i get is the same. It’s a bunch of tables with masked data, and they all want actionable insights, except i feel there’s never enough information to actually find an actionable insight. you can rarely use domain knowledge as identifiable data is anonymised and they never provide enough historical data to see if differences really matter.

Do other people feel this way or have i gotten the wrong end of the stick, if so any advice would be appreciated.

EDIT: Thanks you for the advice in the comments, I think being curious, documenting my process for the analysis I can do and explaining what data I needed to delve deeper is the way to go.

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[u/avxjs]

I don't disagree, but I also don't mind. Because everything is so vague, you can often get away with recommending whatever you want as long as you articulate some reasonable assumptions, lol. Especially for entry level roles.

[u/Saneless → u/avxjs]

Yeah, lay out the assumptions and go from there

Though one time I commented that their data was hard to make sense of because it was scrubbed of useful headers and columns to make it generic for the assignment...

They said that's how their data is. Yikes

[u/avxjs → u/Saneless]

Yeesh. That's a bad sign, lol

[u/r_Yellow01 → u/avxjs]

That is so dumb. The entire data analysis is based on asking the right questions in the first place. Sometimes in five different ways.

[u/avxjs → u/r_Yellow01]

Sorry, what is so dumb?

[u/Droughtly → u/avxjs]

A lot of attempts to anonymize data break the observable relationship between data points.

Let's say the data original collected is income, zip code, and birth date.

Let's say that data is anonymized. The income is reduced to tax bracket. The zip code is reduced to the general area and not the full postal code. The birth date is reduced to birth year.

There's a real correlation in success, sport participation and socialization based on your exact date of birth because it determines how developmentally mature you were compards to your school cohort. A classic example of this is hockey players, whose birthdates cluster around the winter for the turn of year cut-off that set them to enter pre-school or kindergarten, and by extension sports programs, developmentally older by almost a full calendar year.

When you're missing this information, you can draw incorrect conclusions where models based on your work fall apart in real life. Say with the income being reduced to tax bracket and zip to general area, the neighborhood to neighborhood data can reveal a trend in school taxes, student income, and ultimate financial outcomes. With it absent, you can look at school a and b in the same city and conclude that one us doing worse because of income when the parents actually cluster closer together when accounting for what end of each tax bracket they cluster to, where the real issue could be students showing up later consistently due to a more circuituous bus route to one school.

In real life, the data has infinite dimensions, and the best analysis comes from accounting for all possible confounding factors.

[u/avxjs → u/Droughtly]

Not sure why you're lecturing me... Was looking for clarification from the person I responded to. I am not an entry level analyst. Like I said, I don't disagree that it is a flawed process. But it is what it is.

[u/Droughtly → u/avxjs]

I wasn't. I was answering your question.

[u/avxjs → u/Droughtly]

No, you weren't. I was asking the person I was replying to if they were calling my comment dumb, or the interview process dumb, because that would inform my response. 

[u/Droughtly → u/avxjs]

Hmm, yes, I was?

You were talking about the specificity of data not mattering, but the arguments. They said it was dumb because the specificity matteres. You asked what was so dumb. I explained why the specificity of data matters.

I used very apolitical and bland examples of ways anonymizing data can do this, rather than specific ones. I don't care who you are, you said something incorrect before, were corrected, and you asked as an argument after their reasoning. Your point seems to boil down to, I'm not the person you addressed specifically. But you didn't make a DM, you posted a comment on reddit, so that's irrelevant.

[u/avxjs → u/Droughtly]

Okay, sure. My initial comment was a bit tongue in cheek, but the point I was trying to make was that in the context of an entry level interview, where you are intentionally given incomplete and anonymized data, it is acceptable to make reasonable assumptions. I wasn't making any comment on general best practices. Like I said, I don't disagree that it's a flawed process.

ETA -- I did not ask for "an argument after their reasoning" I was literally asking if they were calling me dumb, lol.

[u/Aggravating_Sand352 → u/avxjs]

Anything with an exact answer can be solved with AI so the approach needs to be this way.

[u/Winter-Technician-63]

I would imagine they're way more interested in your process than the actual insight that comes as a result of the work you do. I would just relay a few even semi-interesting findings and do a great job documenting how you got to that finding and that will get you a next interview (assuming your process is solid).

[u/Yazim]

I think those are the most interesting questions to bring back in your analysis. Just say that you wanted to do X, but the data wasn't sufficient for that, but here's what you did find or would dig into more once you had access to the full data.

And also, giving homework during an interview process is dumb, pointless, and poorly thought most of the time.

[u/chickenshrimp92 → u/Yazim]

This is what I did during the interview for my current job.

I kept metnioning that I found X,Y,Z interesting and if I had more time and resources I would love to see how that relates to A,B,C which could lead us to some real big insights.

It shows you understand the data they sent you and are already thinking months down the road

[u/GamingTitBit]

Yeah I had a data science interview like this. Huge table of data which was very sparse. Task was to build a classifier. Was sooo vague. I built one, it was not great, got like 60% accuracy but I wrote a whole slide deck of what I would improve and investigate.

They didn't go with me but I asked them what I could do to improve, they told me my slide deck was the best and infact my accuracy score was the best also. Who knows why they said no. But they went nearly bankrupt 1 year later, so I guess I dodged a bullet.

[u/FIBO-BQ]

Last company i worked for, I had to sit in on the process, judge these take home things, and give feedback. This was before GPT and other AI tools.

I looked for a few general things. Did you show the basic understanding of how to use the tool? Was it readable? What did you say when you sent back, any follow up questions? Good write up of the analysis?

If so, congrats, I said lets talk in person.

Now that Im a hiring manager and AI is everywhere, I would rather talk and see how your brain works. I would never give an assignment.

[u/my_cat_wears_socks]

I used to be a hiring manager for marketing analytics and we had a case study as part of the process and yes, it was tables with somewhat-masked data.

The “actionable” insights they’re looking for are fairly generic. For marketing it’s stuff like “recommend increasing spend in Channel X, decrease focus on Channel Y because…” They typically just want to see if you’re capable of taking data and turning it into business-relevant words. These types of things are usually made to not require domain knowledge of the specific industry, just of marketing (or whatever type of data you’ll be working with) in general.

[u/Suitable_Rabbit6016]

These tasks seem more about showing your thought process than finding some perfect insight explaining what data is missing can be just as important as the analysis itself

[u/Narrow_Rutabaga_6634]

As a hiring manager - I'm more interested in how you probe the data and the questions you're asking even if you don't have the answers. Curiosity and communication are the most valuable assets you have in an age where AI is covering more of the technical side

[u/Peachy1234567]

When I was hiring I intentionally would give them only a very small slice of the data. This is because 1. As others noted I was more interested in seeing their thought process, 2. I wanted to limit how long they could reasonably spend on it. If I ever get to hire again I’ll try to move away from take homes though, they suck.

[u/fang_xianfu]

Yup, I don't do take-home tests any more. Interactive whiteboarding all the way - an hour with some vague problems and some tools to solve them. It's more analogous to real life.

Data Engineers, I do do a take-home, but not for analysts.

[u/plantaloca]

At this point in my career, I’m more interested in the richness of data (metadata) instead of looking at raw data only. 

To scale, analytics needs a shared understanding of what we’re measuring. If what you get is data with not descriptive names (tables/columns), lacking a data dictionary, and vague context of the goal then what they’re hiring for is someone who will conduct analysis blindly. 

You don’t want to be part of that pack. You want to be someone that can think for themselves. Offer a better structure of their data, with clear labeling, metric descriptions and inputs, and formulas along with whatever insight you seek to pursue. 

Then you might show that their poorly maintained  data needs X, Y and Z, to be defendable against scrutiny and transparent enough for traceability. 

[u/Choice_Role_8291]

What’s really fun is crushing these interviews only to get beaten by an internal hire. Happens every time.

[u/NightflowerFade]

How useful are these tasks nowadays? Practically speaking you just feed the whole thing through Claude code and call it a day

[u/Prestigious_Age_6740]

A technical interview is looking to see how you handle ambiguity just as much as whether you know the right answer, because that's how things are in the real world. Write down lots of follow up questions and assumptions. They want to know that you're not going to melt down when you're not sure about something.

[u/Natural_Ad_8911]

If that's all the info you get, that seems a poorly worded question.

Actionable by whom?

It may be intentionally vague to test your processes.

I'd start by laying out the problem and any gaps you see. List the assumptions necessary to bridge that gap and then proceed.

If they haven't even specified the audience making the actions from their insights, you can list a few you could imagine and then pick one to delve into.

[u/ArielCoding]

Don’t just list what’s missing, pick a real answer, say assuming X, I’d recommend Y, then add one line on what you’d check to confirm it, that shows you can decide under uncertainty, not just spot the gaps.

[u/SprinklesFresh5693]

The first thing you do is start plotting the data.

I have never had any interview of this kind, but do they at least tell you what do the variables mean?

[u/FinishGlum2309]

they're basically testing if you can say something reasonable without panicking, not if you can crack the case

[u/Brighter_rocks]

i dont give tasks like this at interviews

[u/Fine-Ad-1732]

Tempos atras passei para a entrevista c o gestor de uma grande cia de telecom explicando que o histórico de dados disponibilizado era curto demais para explicar sazonalidades anuais “como fazer isso se te passam só 9 meses?” expliquei por intermedio de 2 cenários os possíveis comportamentos dos números adotando algumas hipóteses e deu certo conduzir assim, acho que as vezes querem quem consegue abstrair e conduzir hipóteses…

[u/Super_Math3890]

Sounds like a Kobayashi Maru

[u/Creepy-Square281]

Learn what you can from the data. Find the important metrics - use your common sense, sales volumes are important, not sure what your data looks like. How are the important numbers trending? Can you put the numbers into various groups and see if all of the groups are trending the same way, or is one group stronger than others, etc.
Let's say its web log - figure out what's getting more traffic, less traffic etc. Do they tell you the device, or what geo region the traffic is coming from? group metrics by whatever slices you can.
Look for anything that is some kind of code. get trending sums for key metrics by code.
I'd say actionable means pointing them in the right direction. They know what they've given you won't result in final solutions.

[u/PepperIcy4822]

Yeah the vague take-homes are basically a test of how well you can BS a narrative around garbage data. One thing nobody mentions: ask them upfront how long they expect it to take and stick to that, because the candidates who spend 15 hours polishing usually lose to the ones who turn in something solid in 3 and flag the tradeoffs.

[u/Mitchhehe]

It’s better than hours of STAR questions, be careful what you wish for

[u/SpecialistClassic937]

plot twist their actual production data is exactly this useless and they just want u to hallucinate revenue

[u/naijaboiler]

what magic insights do people expect. most meaningful insights require deep domain understanding

[u/chips_and_hummus → u/naijaboiler]

you’re missing the point, and thus exposing information about yourself as a candidate

they’re not expecting magical insight

they want to see how you think through and structure analysis, how you document your watch outs, what other information you would need to take it to the next level, etc etc. 

if your primary reaction is “i can’t do this with the constraints you’ve given me”, just know that the next candidate is doing the best they can and explaining what they’re doing, why, and the limitations

then ask yourself which candidate you would hire

[u/naijaboiler → u/chips_and_hummus]

I am usually on the hiring end. my bigger fear is not the person that can't think structurally, those are easy to filter out, its the person thats overconfident in their limted knowledge and doesn't have healthy respect of knowledge from non-data business persons.
so over-claiming from incomplete or unavailable information which this type of take-home encourages is exactly what I do NOT want. A test that doesn't even have enough to test that is really useless to me.

[u/chips_and_hummus → u/naijaboiler]

uhhh you should easily be able to express limitations and assumptions and how that impacts your level of confidence in your findings with this type of take home

[u/naijaboiler → u/chips_and_hummus]

But when the test is missing so much that you can't say anything at all. What's the point. 

[u/chips_and_hummus → u/naijaboiler]

everyone’s getting the same test. they all typically have enough to do basic analysis and thought processes on. 

it’s weird to assume these tests have 0 content to say anything about

i’ve never seen anything like that 

[u/naijaboiler → u/chips_and_hummus]

Like i said, I'm rarely in a place where in filtering if the person can do the basics. It's more like their judgement and posture I'm usually tl wanting to evaluate. A test that's missing too much is useless for that

[u/chips_and_hummus → u/naijaboiler]

fortunately most sql tests aren’t missing that 

[u/liftingislife19]

Lmao if an interview asks me to do a “home task” I am dropping out of the process.

Is this a junior level thing?

[u/Thrillhouse763]

I refuse to do take home tasks. I'll show them my portfolio.

[u/Nearby-Cockroach8655 → u/[deleted]]

Wow super insightful

[u/Anybody220 → u/Nearby-Cockroach8655]

Well, it definitely wasn’t insightful, but they aren’t wrong.

I get 3,000+ applicants when I post a job, and only about a third are actually qualified. At that point, a resume alone isn’t enough to find the right person.

I sort the qualified resumes into three groups: average, good, and great. The “great” candidates get the first assignment and an interview slot. I typically have about 50 interview slots, so if I don’t have 50 in the great group, I pull from the good group.

The first assignment is intentionally basic like counts, sums, simple statistics, and so on. I have them use whatever program you want, just not Excel or VBA. About 50% don’t complete it and some respond with “see resume/portfolio.” Those go straight to the trash.

From there, I narrow it to 5–8 people for a second assignment and presentation. That’s where I’m looking for useful insights beyond the obvious, while still expecting basic accuracy.
Ultimately, I’m trying to see if this person can work independently, be accurate, communicate, and not need to hold their hand. Also, you need to be curious in the field, so I hope to see something a little beyond what I ask for.

Also, before you think we are trying to get free work, no. I am using 10+ year old data that I and hundreds of others worked through. I got the answers, I just need to see if you can get them to while enjoying doing it.

The final interview is with the 1–3 finalists, my boss, and the team. No assignment at that point.

[u/Nearby-Cockroach8655 → u/Anybody220]

My strife comes from tasks asking for an “actionable” insight when, in my opinion, the data is too vague to produce one without knowing the inner workings of the company. There’s definitely interesting findings available in these tasks but nothing i’d call actionable.

[u/Anybody220 → u/Nearby-Cockroach8655]

I think you are over thinking it. Take the interesting findings, and apply it to a department you think the company has and state how you’d present it to them.