Lately at work I’ve been interviewing for a couple open roles and consequently subjecting the GP server to my rants about annoying or misguided things applicants do. brightobject suggested writing a thread in case any job-hunting forumgoers find it interesting (plus it’s been a couple years since the last job thread). For the record, I’m not a recruiter or in HR — we’re hiring for data analysts and I’m a lead on the data team, so I’m heavily involved in the interview process. Also keep in mind that my opinions are coming from a very specific perspective — I work in mobile gaming, my company is smallish (~40 people), and we don’t use any automatic filters or AI to evaluate applications.
General thoughts
- We were getting around 50 applications every day. Since we don’t do any automatic filtering, we would often need to temporarily close submissions to catch up on our backlog. You could be the perfect candidate but if you miss that window and we find a good candidate in the backlog, we’d never know about you.
- Similarly, if you’re the perfect candidate but you apply two weeks after another good candidate who’s now in the third stage of interviews, we might not make them wait just to learn more about you.
- Rough breakdown of applications I’ve read: 70% ChatGPT ramblings from unqualified people, 25% ChatGPT ramblings from qualified people, and 5% earnest and likable-sounding people who really want to break into the gaming industry but are tragically not qualified. It was so sad to be like “omg these words are written by a human yay!” and then immediately “noooo they have no relevant skills” :(
- Weirdly a lot of applicants sent in resumes that were more than one page long. Not good.
- Some of them used the tiniest font size to fit everything into one page. Also not good.
- No exaggeration, some people would have ~50 bullets under each previous job for seemingly every type of task they ever did. Even unimportant stuff like “attended daily standup meetings”. I am just not going to read all of that. (I imagine this is more useful if the place you’re applying to is using auto filters so you can get through as many as possible, so I get it...)
- I wouldn’t waste time making a colorful sidebar and picking a fancy font and stuff. The more simple and standard it is the easier for me to scan through — I'd love to get through a resume in 10 seconds. Personally I think a sans-serif font designed for screen reading is the nicest (because I spent my youth poring over Verdana font on fanfiction dot net).
- Some people paste the logos of their Lean Six Sigma and AWS etc certifications on their resumes… I do not value these at all.
- Common advice I see online is to quantify your impact by saying things like “provided recommendations that led to a 17% decrease in churn” and “optimized code to improve speed by 32%”. I think this is good advice but sometimes people take it way too far. Like every line would have a number in it regardless of whether it was a sensible metric. I saw someone write that they “attended daily standup meetings, increasing team communication by 20%”. Like… my takeaway is that you’re on a team of 5 and you being 1 of 5 people talking in the meetings is 20% of the team communication. Be serious…
- One kinda cunning but sinister thing I encountered reading resumes this year… there were a few times I was scanning resumes and got excited because the applicant’s most recent experience was super relevant. Gaming analytics, forecasting customer LTV, making visualizations to help the design team make decisions about features in the game, all these nice keywords but wait — all these bullets are under (e.g.) famous non-gaming company “Wells Fargo”. I go to their LinkedIn and see a totally different description for their Wells Fargo experience, one that actually makes sense for Wells Fargo. Eventually I realize the super relevant description is just from ChatGPT rewording our job posting and the applicant is programmatically injecting the ChatGPT-rewritten job description into the bullet points of their most recent work experience. Wow. It’s impressive and probably works really well against companies that use auto filters / AI to screen applications, but it sure is a pain for me on the hiring team.
- Some people include interests and hobbies on their resume if they have room; personally I think this is cute. Doesn't affect my decision but it's fun to read.
- Where you went to college doesn’t matter to me. An applicant from Harvard looks the same as an applicant from the local community college. The number one thing is relevant work experience. For fresh grads I’ll look at projects/internships, skills, relevant education, and generally whether they seem responsible or proactive. GPA and test scores I ignore.
- In my experience, so much of a job is working with other people. At work I need to talk to product, UA, engineering, production, QA, execs, finance, design, and the other people on the data team. Being able to have productive discussions with people, pushing back on unreasonable requests, suggesting different ways we can solve stakeholders' problems... these are hugely important skills that I think applicants overlook. I feel like most applicants can write decent code, but few can develop a great working relationship with their stakeholders. People who mention how they work with stakeholders on their resume or elsewhere in their application get a huge boost in appeal in my eyes.
- This isn’t a required part of our online application and there’s zero expectation from our end that people submit one. I’d say like 2% of applicants included one.
- I’ve never moved an applicant to the next stage purely off an outstanding cover letter, but I do reject applicants based on bad ones. Bad = they write how they’re excited to apply for [a different company’s name]. It’s an honest mistake I get it, but I have 100 other applications to read so the moment I see something disqualifying I’m going to reject and move on. Also it suggests you don’t proofread important work.
- When we were hiring a couple years ago, every cover letter I read started with the same idea: “I’ve always loved video games ever since [favorite childhood game]”. Back then I was starting to roll my eyes at how cliche it was but nowadays almost nobody mentions liking video games at any point in their application! It’s not a good or bad thing, but I do feel like it’s an easy thing to mention to earn a couple brownie points (even if it’s not true), so it did surprise me how rare it is now. Probably because it’s all automated applying.
- Our application form also includes 2-3 questions like “what do you think is the most important metric for mobile gaming” or “what was a challenge you faced on a recent project and how did you overcome it”. No right or wrong answer, no essay required, just looking for a couple sentences to learn more about the applicant.
- In reality I just learned more about ChatGPT. People, ChatGPT responses are sooooo obvious… after a couple days of reading applications I became able to distinguish 1) people pasting in ChatGPT responses verbatim 2) people using ChatGPT but rewriting it into their own words 3) people actually independently coming up with an answer. I wanted to cheer seeing the last one, it was so rare.
- Ways I could tell it was ChatGPT pasted in with no effort:
- One of our text boxes had a max character count of ~250. The vast majority of applicants pasted in a response that cut off halfway through a word. Sometimes that word was “analysis”.
- A lot of applicants literally pasted in the “ChatGPT says:” part into the text box.
- At one point we tested including a question about your proficiency in certain languages and tools, and some of the responses came from the ChatGPT POV. Like “I can assist you with writing code in Python”...
- Full of “bolded” headers, like
Code:
**Data cleaning**
- Sometimes ChatGPT just makes up stuff. Like they write an interesting paragraph about their previous experience using x tool or working in the gaming industry, and I go check their resume and LinkedIn and they have no previous experience using x tool or working in the gaming industry.
- The exact same phrases appearing over and over again. The phrase “Day 1, Day 7, Day 30 retention” appeared in almost every response — the exact same capitalization, numbers, and punctuation across a thousand applications. The exact phrase “The complexity arose from the sheer amounts of unstructured data” appeared across a thousand applications.
- In general the answers are just SO long, SO vague, and SO buzzwordy I can feel my brain turning into soup trying to follow them.
[4:24 PM] pluv: basically the chatgpt stuff is like
[4:24 PM] pluv: "i will leverage my expertise in machine learning to accelerate the data-driven decision-making processes and enhance player experiences by uncovering actionable insights to increase player engagement, which will optimize the company's success"
[4:26 PM] pluv: where like the semantic value-to-buzzword ratio is basically 0 lol
[4:26 PM] pluv: my time gping smogon analyses really prepared me for this.
[4:26 PM] Hulavuta: yeah it has a lot of words and doesn't really substantiate anything
[4:26 PM] Hulavuta: that's what i noticed in student AI papers
[4:27 PM] Hulavuta: like "Blade Runner brings up questions of what it really means to be human"
[4:27 PM] Hulavuta: like ok what are those questions and what is the answer
[4:28 PM] CryoGyro: "i will leverage my excellenat STAB combination in the OU metagame to accelerate the wallbreaking processes against anything that doesn't resist it and enhance player experiences by uncovering switch-in opportunities to increase player engagement, which will optimize the teams that appreciate the breaking ability provided by me"
[4:28 PM] pluv: lol. exactly cryo
- Sometimes I would see someone write real human answers to most of the questions, with spelling errors and poor capitalization and so on, and then have one perfectly written robotic answer. Like obviously you asked ChatGPT for an answer on that one question lol.
- A lot of automated applications seem to just put “NO” to every question or “YES” to every question. I saw stuff like…
- “Do you have legal authorization to work in the United States?” “NO”
- “What interests you about working here?” “NO”
- “What is a key metric you tracked in a recent project?” “YES”
- Not much advice to give here, either you have the skills or you don’t. I guess if it’s a take-home thing where you need to make a presentation/report/slides/etc take a little time to make it pretty and reader friendly! If it’s a live code test over video call or something, it can be nice to talk through your thought process as you’re writing the code.
- It’s not a dealbreaker but it’s a little sad when people sound super rehearsed like they’re reading from a script. I feel like if you’ve already made it through multiple stages, then the hiring team trusts your technical skills and are mostly trying to suss out if you’re a weird asshole or a chill nice person. So being friendly and personable should be the goal imo.
- So many people just… don’t answer the question we’re asking. They answer some semi-related question that isn’t our question. A couple years ago we were hiring for a data analyst focused on user acquisition and one of our questions was “what’s a marketing campaign you’ve seen out in real life recently that you thought was effective” and everyone except the guy we hired talked instead about marketing campaigns they worked on at their job. If you consistently don’t answer our interview questions then I have to assume if we hire you, you won’t answer our work questions either.
- When it’s time for the applicant to ask the hiring team questions…
- You want to make it sound like you are not desperate for any job. An interview is also the applicant getting a sense of if they want to work for the company, not just if the company wants to hire the applicant. Have some real questions that suggest you want to know what it would be like to work at the company. What would I be working on in the first week, first month, first quarter... What percent of the work week is dedicated to meetings vs working with engineers vs building reports vs ad hoc analyses. What’s an exciting project the interviewer has worked on lately. What qualities make someone in this role successful.
- Questions about the company’s vision and future goals and the industry etc also suggest that you want to learn more about whether the company is a good fit for you. “I noticed your latest game doesn’t have ads. Are you planning to introduce ad monetization or is there a reason you haven’t implemented it?” “The industry seems to be moving toward x trend, how does your company feel about it?”
- In previous years I’d hear applicants ask about company culture, but no one has asked that this year — maybe because of the shift to remote work? I think it’s a fine question to ask still.
- Whenever I see a Reddit thread about asking questions at job interviews one of the top comments recommends asking “do you have any remaining concerns about me as a candidate that I can clear up for you”. I think this is a HORRIBLE QUESTION. It’s so bad that I almost think people write that to sabotage other job applicants.
- In dozens of interviews I’ve never heard a good candidate ask that question.
- You sound desperate for approval.
- You're wasting your chance to learn more about what it'd be like to work at the company.
- If I’m on a panel with another interviewer, we want to get on the same page before we tell you what we thought about you.
- If I had concerns about you, what am I supposed to say? “Yeah your skills in x topic were lacking” is awkward and secondhand embarrassing, I don’t want to hear you try to justify yourself or apologize when I already know your skills in x topic are lacking.
- Also if I had concerns about you, I would have already followed up on them during the interview.
[3:20 PM] pluv: i feel like the question assumes this kind of scenario happened
me: [question]
them: [answer that seems bad]
me thinking to myself: hmm that's weird. oh well. next question
when this is actually what happens
me: [question]
them: [answer that seems bad]
me: oh that's interesting, when you say [x] can you explain that a little more?
them: [still a bad answer]
me: i see, what if there's a situation where [y] happens?
them: [still a bad answer]
me: hmm maybe i should clarify that [z]
them: [still a bad answer]
me: got it, ok next question...
[3:22 PM] pluv: i've already learned something about you from that interaction, i don't need to clear up any additional concerns about you
Anyway, that’s all I can think of for now! Again, this is all coming from a very specific perspective and won’t apply to most hiring situations, and I'm sure some of the things I complained about are reasonable and effective in other hiring situations. I hope in spite of that someone can derive some value out of this post

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