ATS Myths: The Truth About AI and Your Applications

Turn off my phone. See. All right, looks like we are live on YouTube. I don't see us on LinkedIn yet. Don't see us on LinkedIn yet. Not seeing— unless LinkedIn has a serious lag. Okay, it probably does. Okay, I think we are, we are live. Okay, if anyone is in the building, please, um, Let us know if you can hear us. Can you let us know if you can hear us in the chat? Test. All right, thank you, JC on the YouTube. You're testing, you're testing. All right, JJ, thanks. Okay, where, where are you guys posting in the chat? Where are you guys watching from? Um, I am calling from the great state of Alabama. Emily, where are you? Where are you calling from?

I am located on the west coast of Mexico, so I am located in the state of Nayarit.

Okay,

the great state of Nayarit. And if, uh, for any of you guys who are either, you know, from the region or have traveled to Mexico, it's about About a 3-hour drive from Puerto Vallarta. So like people where, where I come from, it's like when it's really cold and snowy in the winter, they kind of like come down here and hang out. I'll be waiting for you. See you at the beach, guys.

I would definitely go to Mexico, but I, I don't speak, uh, the language over there.

Well, there are certain parts of Mexico where you don't have to. Like, English is super widely spoken in Tijuana, Puerto Vallarta. You can totally, uh, I think all the big vacation spots. Um, what am I thinking? Cancun.

Uh, I don't really like the big vacation spots anywhere. Like, my family's Jamaican and I hate going to like the resorts. I'm like, that's just too— like, I came here to be— oh, if I want to be around like a bunch of like Vacationers. I definitely— I don't know, I feel like you don't get like the sense of the, the actual like country resort places, you know.

Then you should go to our local beach, San Blas. It's like mostly Mexican tourists there.

Okay. Um, Kate says she has friends who live in Merida. Um, they don't speak the language.

JJ's in Texas.

Yes, Texas. Georgia is in the house. I wonder what part of Georgia. Um, I will be in Georgia, um, around December. I will be in Atlanta, uh, if not earlier. Texas is in the house. Texas is always in the house. There's so many Texas folks. I think Data in Motion community is 85% from Texas. That is just a guess. Great. Um, thankfully we haven't had any Dallas Cowboys fans join, so— Fayetteville, Georgia! Yo, I'm from Fayetteville! Get out of here! Get out of here! I went to— I went to Fayette County High School! Get out of here! First time I've seen— okay, all righty. That's— that's a first. I've never seen a fellow Fayetteville, Georgia person like live. Yeah, I, I— yeah, Fayetteville is like a second home for me. Lawrenceville, Georgia in the house. Okay. These are, these are places that I am familiar with.

Okay, anybody from the Midwest today?

Midwesterners, Midwesterners, show up! Where, where's, uh, Midwesterners?

Where's Dylan?

The Wisconsins, the, uh, the Minnesotas, the, uh Missouri, Springfield, Missouri. Okay, okay, okay. All right, uh, sorry. Yes, listen, uh, I hope, uh, Dallas Cowboys fans are mourning the Micah Parsons trade. Um, as a Giants fan, I really don't care, but I know that you guys are sad. Um, I guess that's an inside joke for Cowboys fans and football fans. Sean, are you a Cowboys fan? Okay, maybe we're going a little too long. Okay. All right. So we are ready to go. Where is that? It's about 6 after, so we can get started. All right. So we are here to talk about the myths about ATS, the scary, somewhat unknown. I think most people think that, hey, I submitted something. It didn't— I'm not getting interviews because I can't beat the ATS, but we We are here to debunk myths about the ATS today, Emily. But before we get there, how about we introduce ourselves just in case we got folks who are just seeing us for the first time? My name is Kedeisha. I help people become data analysts without going back to school. And I run a community that I've been running for— I've been in the data community for like past 4 years. And I've been, you know, running a community of over 60K. All right, go Niners. San Francisco's in the house. And we are here to give you guys, you know, break down the— how do I say it? Pretty much break down the barriers and break down the gates. We don't do gatekeeping here. So you guys can have more ROI for the time that you guys are spending in your career. And Emily is our star of the show. Emily, you introduce yourself and how you help folks get great jobs.

Sure. And before that, I just have to say Pedro was supposed to be here today too, and we're missing Pedro. So he's not feeling too well today. So we'll see him again next time. Pedro, we miss you. But for me, so my name is Emily. I am a former Wayfair recruiter who hired for mainly analytical roles at Wayfair. And more recently, I have used that experience to pivot into reverse recruiting and career coaching. So right now I work with job seekers who are looking for their next role in tech. And, you know, my specialty is data. So I love the data community. It's always fun to, to be here with you guys.

Data community is the best community. And, you know, before we start, let's listen. I think this is something that— this is a sentiment that many people share, right? I've tried everything. I've added all the keywords in the world. I've modified my resume to each job post. I followed up with recruiters after applying, and I still hear silence.

Right. I mean, I would love to know a little bit more about that. It's really hard to give like a blanket answer when, when something's not going right. I mean, there are a million things that could be going on there, starting with the resume format. Is it not getting parsed into the ATS system? Because it's like the format's not good and the ATS is having a hard time with it. Are you missing a skill? Is there a skills gap there? I don't know anything about your, your background. Are the roles that you're applying for really strongly aligned with your skills? Do you have an industry match? Um, I mean, there are so many different things that just based on, based on the question, like, it's really an individual, an individual topic that I think needs to be— um, okay, you already have 3 and a half years of experience. Good question. I would need to dig into it a little bit more, to be honest, like see what's going on there. So sorry that I can't give you anything more specific, um, off the cuff, but there are just a million things that, that could definitely be going on. But hopefully, you know, some of the things that I'll talk today, talk about you, talk to you guys about today will help you get more of an understanding for what's happening right now with the ATS systems. And maybe that can be kind of ringing some bells when we go through that. And maybe in some future sessions we can talk again about, you know, resumes and what, what we need to see there. And also, I think the last chat we had And, you know, recent chats that we've had about other topics are online on Kedisha's YouTube and also on the old event links on LinkedIn too. So have a look at those maybe and see if there are any tips in there for you.

That, and also, we also will have some goodie resources that we're going to share that will help folks too. Okay, so y'all stay tuned to the end, man. We got some good stuff, right?

We do. I'm excited about that.

All right, so let's kick off. Emily, how are we going to kick this off?

Great. So like, I think I'd like to start by, you know, talking about the implementation of AI in hiring as it stands. So, you know, AI is kind of a thing that hit us like a steamroller. We didn't really see it coming. I mean, of course, it's been in the works for years and years. But all of us normal folks out here, You know, the day that ChatGPT launched its publicly available interface, it was just, I was personally blown away. I hadn't ever seen anything like it before. And it's been like the last, I don't know, 2 and a half, 3 years now that that's been available to us. And now that there are a lot of good models out there, there are so many different tools that are built on these models that the usage of AI for every imaginable, every imaginable business use case has just exploded. So I think that there are a lot of assumptions out there that AI is being used in all aspects of hiring. And you can read a lot of, you can read a lot of, you know, stuff out there that is, you know, maybe not so true about what's going on with the ATS. So that being said, I would like to share just a little statistic with you. Can— there. Okay. So this is actually from the Future of Recruiting 2025: How AI Redefines Recruiting Excellence. So this is a report, a research report that was, that was created by LinkedIn. And of course, like, you know, as we talked about previously, you know, LinkedIn is basically a database. So they have access to a huge ton of hiring data and they're really in contact with the industry. So, and this is also from 2025. So I have a lot of faith in this, in this report. So basically, if you're looking here, like this is the, the, the adoption of GenAI in the recruiting process. And you might be surprised to see that 32% are not using it at all. 31% are exploring. So that's almost 2/3 already who are just kind of thinking about it. So then we come up here to, you know, a little bit over the top third, um, who are 26% experimenting, which means that they're probably still, you know, thinking about it, looking at it, playing with it to see what kind of benefit they can get out of it. And only 11% are currently integrating GenAI into the hiring process. So I don't know what your expectations were or if you think this is low or high. Personally, just hearing about all the news out there about what's going on in the world of AI, I was a bit surprised myself even to see this statistic in a study. However, I do regularly have chats with recruiters like Pedro and the like. And I was really surprised. I've been really surprised about the conversations that I've had this year where I found out that recruiters actually aren't using AI as much as we hear that they might be in the media. So, so that's basically, I think my first takeaway is that it is coming and it is, you know, it is definitely getting more and more implemented, but right now it's still still early days. So let's just kind of see where it takes us. I think we do need to be prepared for it, you know, becoming like more of a reality, um, in our day-to-day lives. But for now, it's like those who are actually using it on a daily basis are very few. All right, I can stop sharing now. Do I have the power to do that? I do. There. Okay, great. So that's the first thing. Then the second thing, so, you know, the headline of our chat today is called ATS Myths: The Truth About AI and Your Applications. So what is actually the ATS? I'm sure a lot of you who are in the chat today are probably in the application process. So you've probably seen the ATS in action if you're doing cold applications. You know, you go to LinkedIn, you search for a job, And then it takes you to the career page of the company. And then you'll, you'll get put into a system like Greenhouse or Workday, or let's see, what are some of the other ones? Jobvite, Lever, ICIMS. I don't know if I'm— if that's ICIMS or, or whatever. But there are a ton of different systems out there that companies use in order to collect, store, evaluate your applications. And also they use this same system most times to communicate with you and move you through the— or move candidates through the hiring pipeline. So basically, you know, it sounds like big and scary, but all it is is basically getting your data in. So once you send your resume, it parses your resume, meaning that it extracts all of the data out of your resume into certain fields in the database. It stores that information, and then it makes it so that your information is available for recruiters and hiring managers to review. So you know when I was a recruiter at Wayfair, I would sit down at my desk and open my. I was using JobVite at the time. There they in the meantime they switched to Greenhouse, but I would open JobVite and I would just see how many new applications. I had gotten in like the last 24 hours. And then I could see, I could see, you know, your name, and then I could have an overview of your resume. And I could move you through different stages. If I liked your resume, I could put you into a pool like liked the resume. If I didn't like your resume as much, you'd probably stay in the general pool. Maybe there were some reasons that I would reject you right away. So for example, I actually didn't do this personally at Wayfair, but I know that this happens a lot in the US. I was hiring in Germany, so that's why some of the experiences weren't one-to-one transferable. But I know that in the US, you know, visa sponsorship is very difficult. So for that reason, you know, if you had visa sponsorship listed and it was a position that we couldn't use to— we couldn't use for visa sponsorship, that would be a reason to automatically, you know, sort people into, you know, the category of not getting an interview. So basically, I mean, it was my way to see, you know, what, what's going on in your profile, and then be able to like move it on to different stages. For— there are a lot of different stages that it goes through, it doesn't really matter. And everybody's workflow is different as a recruiter. My personal workflow for business intelligence was to get get the resumes in, then I would invite people to take a coding challenge. And then after that, if you pass the challenge, then I would personally have a call with you. And I did that for every single person who passed the challenge. And then if I got a good vibe from you, I would pass you on to a hiring manager. So that means, you know, at that stage, the hiring managers also have the ability to see the candidates that I've passed on to them. So they could see everything that I could see, basically the same view, but only fewer candidates because I would just send them the ones that I passed on. So I mean, that's basically all it was. And in the meantime, over the last 5 years, honestly, it hasn't really changed that much. So I could message you, I could look at your resume, could write some notes and comments about you, but that was basically it. So now because of like the availability and the proliferation of AI that's out there, A lot. So what's been happening is that all the job applicants that are out there have the ability to get resumes, like highly customized resumes to companies at like light speed. So when I was working doing that 5 years ago, I would maybe open my computer and I had 100 new applications for a particular role. Whereas today I might actually have like 1,000, closer to 1,000. So just imagine the manual workload of going through all of those resumes. And I don't know if you've seen this statistic online, but a lot of times you'll read that, that recruiters take 7 to 10 seconds to review your resume. I think that absolutely was true when I was reviewing resumes. I probably did spend about 10 seconds per resume just seeing if all the pertinent information was there. And today, if I think that I had if I had to get the same volume of resumes manually reviewed in the same amount of time, I would have 1 second per resume. So it's just not realistic to be able to do anything effective in that 1 second. So because of the volume that, that's achieved and the capacity that job seekers have in getting those resumes out now, companies also have to be doing something to get some of that efficiency back. So, you know, one of the things that, that is available on the market now is AI assistance for recruiters. And there are a bunch of different things that are out there. I'm sure that some of you have probably seen like these interviews. You can do like an AI interview and it'll assess your, your video that you take. It'll ask you some questions. You speak into the camera. There's no human sitting there. And then it'll, it'll basically pass that information on to a recruiter. It probably is doing some kind of ranking. I think one, one of the big, the big opportunities for efficiency gain in the process right now is ranking that just, you know, helps move the, the resumes that are most relevant to a particular role to the top of the recruiter's list. So they're already going through the resumes manually that the AI has assessed as, you know, highly relevant for the role. So that's probably like the biggest efficiency gain that exists. I think there's probably also some AI involved in the communication as well. I don't think that's as important. But that being said, I mean, basically, It's a database, it's a CRM, there might be a customer relationship management tool, and there might also be some kind of AI add-ons which assist with ranking. I think that's basically what's going on. And when I talk about this type of tools, these are the main tools that larger companies are using, like your tech companies that are established, maybe midsize to large. Companies, even like large enterprises are using this type of tool. There also are smaller solutions out there which are like more highly founded in AI. So I've actually been in contact with some founders who are creating tools for companies as well. And a lot of times we'll see that kind of adoption among startups. So if you're applying for a smaller company, you know, they're really agile. They're able to use some cool new tools. They probably don't have a lot of capacity for recruiting. So they have a really strong business need to have speed in recruiting. So they're the ones who right now are more likely to be using these AI-powered recruiting tools than like larger enterprise companies. All right. So that being said, and if you guys, like Kadeesha said, if you guys have any questions as we're kind of going through, I think I would just start by going through some questions. Like, I would say these are probably the top questions that I get around the ATS system. And I don't know, should I like type this question in the chat, or does that— would that be helpful so everyone can see like which question we're talking about? Okay.

I can probably do it on Canva or something and blow it up, but

Oh yeah, I didn't come with a— come with a slide deck today.

Oh, uh, send me— okay, like, uh, maybe you can like send me it and like you can post it in the chat or send it to me on LinkedIn and then I'll blow it up on Canva.

I'll send it to you on LinkedIn. Um, okay, there, I just sent it. Great, did you get it?

Oh,

okay, good. So I'll just start with the first question. So, you know, there's a lot of hype around this question, the automatic rejection. Does anybody think that they've been automatically rejected or they're consistently being automatically rejected by the ATS?

Oh, everyone feels that. Anyone who says no is lying. Everyone says that.

They're

like, oh

my God, that was really quick. Okay, cool. All right, good. So this is a really good question, and it certainly does feel like that. Um, and I would have to say yes and no. Oh, JJ, you say yes. Okay, yes and no. But I would say that this is generally not the case, um, based on some kind of AI-generated output. So Like I, like I mentioned earlier, like if somebody was looking for a role and I cannot offer visa sponsorship for that role, um, then that is like what we call a knockout question. So if you get a knockout question wrong, you're out and I'm never going to have a chat with you. So if I can't support you, then it's just a waste of my company's time and resources to be having conversations with people who really don't qualify based on Unfortunately, bureaucratic constraints. So I think a lot of times when I've talked to job seekers who are from outside of the US and they're looking for a job in the US and they need green card sponsorship, you will see automatic rejections and absolutely expect that. Other criteria, for example, if there's a degree that's a hard requirement, like you absolutely cannot have this job unless you have a bachelor's degree and you don't have a bachelor's degree, out. So those would be reasons to have a candidate get an automatic rejection. So that being said, I would say 99% of the time a recruiter is going to want to review your resume. And especially if they're using a ranking tool, they're going to definitely be looking through all of those highly ranked resumes for sure by hand. It's still still a highly manual process. Yeah, so super rare does happen in some cases. I think that, you know, kind of fringe case right now, there probably are some, there are some companies who are using auto-reject functionalities that come with these new ATS systems or new even integrations into ATS systems, but the majority of the cases, that is absolutely not the case. And I mean, I think just as many people who feel like they're being automatically rejected by the ATS, there are as many people, and I want to say maybe like 100% of the people feel like they've been ghosted. You apply for 100 jobs and you only hear back for 30 of them. Like 70% of the time you're being ghosted. So thinking about it that way, how is the ATS rejecting you? automatically if you're being ghosted. It doesn't make sense. It's a bad candidate experience to ghost someone. So that's on the recruiters. And I don't want to like hate on recruiters right now because, you know, they have— Hate so much ghosting. Yes, I know. Um, so if you think about it logically, if you're being ghosted, you're absolutely not being automatically rejected. And in fact, the recruiter at that point is simply just not clicking on that reject button because then you've got to generate— you can even batch reject people. 100, 200 people at a time, you just click select all, and then it batch sends out like 200 rejection emails. So I would say let's debunk that myth, call it a myth. All right, next, are resumes ranked? And if so, what powers that ranking? So also, again, are they ranked in the system? Yes and no. So, you know, again, thinking about that, that graphic that we saw about who's actually implementing AI in hiring right now, and it's at 11%. So we can say like, if there's 11% of recruiters using these AI tools in hiring right now, maybe it's like 11% of those companies are actually using the ranking functionality. And there are reasons for this. So for example, Amazon, I think this is kind of a famous case that Amazon uses their own proprietary ATS system. So they do not use Greenhouse, they don't use Jobvite, any of these big ones that I've mentioned before. They have their own proprietary in-house ATS. And in the name of efficiency, as they're Amazon, they created a they created a ranker that would rank candidates. And in doing so, they found out that the biases that are built into human hiring were kind of promulgated in that, in that AI tool. So whatever bias existed was carried over because of course it's trained on human data. So for that reason, they actually stopped using that ranker. I don't know what the, what they're using right now. But this was kind of an interesting bit of news around ATS and using AI in the hiring process. So there can also be legal implications. I mean, you can't just— I mean, you can get sued, right? So yeah, you can— like, people are definitely experimenting with this. And I think, like, personally, if I were recruiting, and I even when I was recruiting, I created a ranking tool. We still did everything manually. All the recruiters would, would go in and give, give a candidate in a resume a rating for a particular thing like, let's say, Excel, or we just had a category for tech skills or language skills and we would rate them on a scale of 1 to 5. And then, you know, we would weight those, those criteria and then whoever ranked highest, we would kind of go through and see like, are these actually the people that we want to be speaking to? We found out that they were. And then going forward, we use that system. So I think that does make sense to be using a ranking tool. However, we need to be really sure that when we're using AI ranking tools, that we know what the criteria are and we aren't, we aren't getting those same kind of biases mirrored back to us that we find in human hiring. Right. I see that there are a couple of questions.

Should we—

should we get those now, or—

Sean says, if a candidate has most requirements but gets hit on a knockout question, there are some companies, uh, for, you know, defense, for example, that utilize a silver medal process that place you in a category for other departments or apprenticeship status, so not totally lose you. Oh, well, that's pretty good.

Yeah. And I would say that doesn't even— that's not necessarily correlated to the knockout question because there are some questions that are true knockout questions and then you might be out of the process entirely. But there might also be like other questions or, or a recruiter might find that your profile is better suited for another role that's out there. So then you get moved into another bucket for a different role. Absolutely true.

I'm in the UK for a master's in data science, soon switching to a 2-year graduate visa where no sponsorship is needed. Q, uh, will recruiters reject me? Oh.

I mean, I would say that this is UK-specific. I don't have a lot of experience, um, supporting job seekers in the US. I'm mostly in the UK. I'm mostly US-based right now. Also have a good amount of experience experience in Germany, um, but I, I can't speak to the legal regulations in the UK, so I don't think I'm the right person to answer this question, unfortunately. I would say speak to somebody local.

Yeah, I will say even over here, when it comes down to the visa stuff or the sponsorship stuff, there are folks where they're like, oh, I have like, uh, some sort of visa where there's no sponsorship that's going to be needed within like 2 years or so. But then there's a question that they start adding, like Will you eventually need sponsorship? So you'd still, you'd still, still be a yes. So, um, so that's, that's unfortunate. But

yeah. But you know, a lot of times those like highly technical roles are more likely to be sponsored. So the question about data engineering, I would say maybe on that, maybe.

Or go to FAANG. They seem to, you know, they definitely have the cash for, um, sponsorships.

Okay, JJ, you meet all the requirements. Is that not automatic rejections? I mean, so JJ, just think about, you know, the pool that you're competing against. So if I had 100 and today there are 1,000, like now to be the one out, you know, to be the unicorn out of the 100 was hard. Now to be the unicorn out of the 1,000 is super hard. So I would say, you know, all we're doing with that application is saying, hi, I would like to speak to a human, please. And I think that earlier in the chat, you said that, you said that you had done other things like outreach and stuff. Definitely keep pursuing networking, keep reaching out to recruiters on LinkedIn. You're not going to get a great response rate on that either. But everything you do is, is increasing your chances. You're a data person, you know that it's a numbers game. So, so Just know that you're gonna, you're gonna need to get a lot of volume out there too. Okay, you applied, you applied for a position at 8 and received a confirmation that the application was received. And by 8:35, you, okay, got another email. Okay, I mean, that's absolutely possible. And when I was a recruiter, even if I was reviewing somebody's resume immediately, I would put a delay of like 2 days. For that rejection email, because people think that it's an automatic rejection if it goes out quickly. However, if I just happen to be looking at the at the rec, I have it open, and I just see like oh five new resumes have been pulled in since my last check. I might check check check check, and then I I might automatic like you know I might move them into a certain category. in that moment. So I think it's absolutely possible. And a lot of times there are, you know, outsourced recruiting teams, might be an external recruiter who's in Sri Lanka or India. And so for that reason, evening hours are totally possible. So I wouldn't take that as evidence of an automatic rejection.

All right.

Okay, good. All right, should we move on to the next question?

Yeah, was this the next one, or I added them all on slides, so—

Oh, uh, we can go to this one next, that's fine. Does AI compare resumes to job descriptions automatically? So it can, but it doesn't necessarily do that. So for example, when it comes to a really big one, which is Greenhouse, In Greenhouse's platform itself, it will ingest your resume. And I don't— I think in Greenhouse you never have any additional questions like, was it parsed correctly? Was your data parsed correctly? Whereas if you open— if you send your application through Workday, like a Workday application, after you send your resume, it'll say like, Okay, it'll show you all of the fields, literally what it just copy and pasted from your resume, and you'll see how much of that information got parsed wrong. And it's so frustrating, like the date is wrong, the experience from one is with the other. It's very frustrating. And you don't see that with, with Greenhouse. So, so parsing always happens, you know, based on what's going on in that particular ATS. And Because of that, like, you can opt into certain functionalities. Like, if you're using Greenhouse, there's an external, there's an external partner that they use for parsing and ranking. So I believe, and don't quote me on this, I'm not 100% sure. I think if you're using Greenhouse, you might have to, you probably have to opt into the AI parsing and ranking functionality. So it can do that, and a lot of companies are not doing that. I guess that's a short answer.

Interesting.

Okay, so what kind of filters or tools do recruiters use inside ATS dashboards? That is highly dependent on, um, on what is going on in the, like, in the hiring. So actually, let me bring— what kind of filters or tools? Okay, I've got my, I've got my notes over here. Okay, so it depends a lot on, on what's going on in the, um, in the rec. So, um, so like, what is the most important feature of a candidate in order for me to speak with them. You might see, you know, 5 different important, important qualities in a job description. Like you need to know SQL, you need to know Python, you need to know Excel, you need to know R, and R might be the last thing that you see in the list. And it might be the most heavily used tool. So if you see those, those 5 things, let's say there are 5, And you don't have R, but you've got everything else, and you think, I'm a great fit, I just don't have R. And they've got R in the last position, but it might actually be the most important thing on the list. So if you don't have it, then, then you're out. So, and what kind of filters? Like, there are tons of different filters. Um, you know, I've seen some people who don't have a location on their LinkedIn. Um, location can be a filter, guys. Because let's say I'm hiring, and I did this, I relocated people for work when I was working for Wayfair. And I need to know, is that going to be an expense for me? And if the salary that I can offer isn't great, it's not above the market average, then how attractive is that going to be? And will it be more advantageous for me to be having conversations with local candidates because I know that I'm not going to incur that cost. So, and there might be another job that's like highly lucrative and it's very well, very well compensated. And then I as a recruiter might say, I don't care where this person comes from, I just need a specialist and I will relocate them here at any cost. So it depends highly on what's going on on the back side that unfortunately we don't see. It's a black box. Yeah, so when it comes to, to tools, I mean, rankers are there, filters are there. Think of it like how you guys like rearrange data, filter data, um, sort by different, I don't know, different criteria when you're analyzing data. Same thing going on here.

Interesting. I do want to take a pause and say something. So, uh, we're talking about like how if, you know, whether or not companies are using AI in the hiring process, but I do want to take a just a second to note how like the job seeker, the how the usage of AI into the hiring process of— I recall when, you know, these companies, um, I can't remember any names right now, but these companies or these websites that had these like AI automated, like you can, you know, create a resume that matched each job and, you know, in a second they will auto-apply for you. And I remember then I was like, oh, this is going to be a mess. So it's like, because now we think of like, we saw like, oh, you know, because it seems like now you can't really trust a resume because if anyone can use a tool that will take your resume and a job description and just automatically match it to it. Like someone mentioned, like earlier, like, oh, I'm doing everything right and still not hearing anything. Well, I mean, just in general, like when a, a new tool such as AI comes into— comes available, so access to it, um, when the masses— when the masses have access to it, it's no longer The advantage that it was at the beginning because now everyone's doing it. So now you have to kind of do more on top of it. Just in general, now we're talking about making custom GPTs when before we were just talking about how do you create good prompts. So it's all a mess. When we talk about parsing and things like that, it's crazy how you can have 20 people who who can submit a resume or use AI to literally look the same or look perfect for the job, when probably 2 are probably perfect for it, but they all look the same. Yeah. Yeah.

And actually, that is a really good point, Kadeesha. So I was actually on a call with a large tech company. It was a public call last week. And their HR or head of Head of talent acquisition or head of HR was giving a, like, a general— yeah, like a general talk to the public about, um, about what's going on in hiring and the use of, like, AI and, and all the things in hiring. And they said, like, you know, what has happened since all of the job seekers have gotten access to these tools is that now, like you said, you know, somebody can come up and make a Somebody can come up and make a, like, perfectly aligned resume with the job description in 10 seconds. They send it out, they just forget about it, and it looks so good. And the recruiter sees it and they get so excited to have a call with this person. And then they get the person on the phone and it does not reflect what is on the resume at all. So you are absolutely right about that. And then that is a huge loss of efficiency because You know, if I'm taking 10 seconds to scan a resume, you would have been out previously if you had just told the truth. But now, like, I'm getting you on a call and I'm wasting half an hour of my time. It's like, it's really, it's really tough. So for that reason, I think going forward, there will be more kind of AI on both sides. And actually, you know, to your point, Kadeesha, I have hated these things. And for that reason, I actually started working on on a solution for job seekers that gets a highly customized and also highly accurate resume out. So, I mean, quite honestly, like, if you're the job seeker, you're having that call. I mean, imagine you're applying for a company that is called like Moondust and they do something. And then the AI tool talks about the time you went to the moon. And then the recruiter sees that and they're like, whoa, tell me about the time you went to the moon. And then you look at the resume and you're like, what does it actually say here? That is embarrassing. Like, I don't want to be on that call. I would rather just get that rejection email, to be honest. So yep, the struggle is real.

Troy, there's a difference between using LLMs to polish your factually accurate resume and using LLMs to lie on your resume. Well, here's the thing, Troy, most folks are doing the the latter. Folks just don't care. They're just, especially when you're mass applying, things like that. There's a difference, but most folks just aren't doing the latter.

Yeah.

And honestly, do people even know if they're lying? Let me say this. Even in the terms of even now, even when I onboard new students in my program, they're like, I don't want to put SQL yet on my resume because, you know, I don't really know it yet and things like that. Um, and I remember like years ago, like in the pandemic days, man, there were like YouTubers and whatnot saying, listen, just, just take this tutorial on YouTube and just put it on your resume and you'll be fine.

Mm-hmm.

Um, and there's some people, there's a lot of people that still kind of operate in that lens. And then like what you said and then what Pedro said, you know, months ago that, you know, you say, you know, SQL or whatever, And then you get on, you, you get the right, you get the interview and you just completely bomb. Like, I don't think people like understand, like when you say, or when you put proficient in XYZ, they're going to expect you to be proficient in XYZ. Um, if you get there, but you know, I guess it's a lining.

Yeah. And I think you've got to just like judge it. Like, what are you comfortable with? Like a lot of people will say, like, I'm not putting that on my resume. Well, okay, you're not going to get the interview. And that's, that's your choice. So you can submit that. And I've also heard stories of people who, you know, didn't know whatever programming language, put it on the resume, and then they got the interview, and then they learned it over the weekend and got the job. So it's like, what are you personally comfortable with, to be honest? I mean, I would say tend towards telling the truth. If you know that you can learn it over the weekend, honestly, I would tell you to do it.

You know what I mean? Whatever it takes for you to get comfortable. I mean, there's some of us that are just, uh, A-players when it comes down to like learning quickly and things like that. Um, but at the same time, if you really think of it in steps, you learn the skills, then you apply it. Sometimes we're just not ready for the application stage, and that's okay. I think being honest and maybe taking like certain, certain like skill assessments is super important so that we're not wasting time.

Yeah.

Applying when we're like, you know.

And which is why I think the projects are super important. So if you guys need some projects, I think that's something that Kadeesha can really help you on.

Um, okay. As job seekers, we have been constantly told it's a game of numbers. I think there should be additional measures in terms of extra screening? I mean, currently it's both. Like, there is the numbers game. Like, uh, one of the coaches that we have at the program, he, he gets a lot of interviews and he does the numbers game too. But at the same time, there is extra screening. Like, he just did an interview where he had to do a case, a live data analytics case study. This was at a Fortune 500 company, live data analysis case study, um, in person. And he had to take a data set, And then he had to create a slide deck presentation in an hour.

Well,

that would, that would destroy 98% of the candidates. So yeah, there's definitely extra screening going on.

Yeah. Yeah. And I think just because of the AI resume situation, there does need to be some, some truth brought into the, into the hiring process. So yeah, additional measures like those, those video interviews, can't really fake that.

Yeah, live. I think live, live case studies and things like that, I think is going to happen more often because I mean, even now, if even with take-home assignments, you can put it in GPT and just spit out something, but you cannot be at something live.

Yeah. And for some companies, like that's going to be a skill that they're assessing on, like, can you figure it— like you have no knowledge of this. Can you figure this out in the hour using ChatGPT? Or are you— do you suck at prompting? Like,

that's it. That's a good skill too. Yeah. Let's see how— yeah. Okay. Um, did we cover this or no?

Um, oh no, we haven't. This is a really good question. Do recruiters manually read all resumes that pass parsing? Very good question. Um, I would say maybe. So do, do recruiters manually re— uh, read all resumes that get an interview? That I would say yes. Absolutely, yes. But do recruiters manually, manually read all resumes that pass parsing? I would say probably not if they're using a ranking tool. So if you've been using a ranking tool, you've got your 1,000 applicants, and you find that the ranking tool works pretty well, and it's never— it never makes sense for you to, um, to have a look at the bottom 10% because they never get an interview. Then I think that's pretty good data going forward to say that we can, you know, from a business perspective, we can be rejecting those, you know, those 100 people automatically without reviewing their resumes. Probability is so low that somebody in there, it's like basically zero that they're going to get the job. So even, you know, I've been talking to some recruiters who even very recently worked for FAANG companies. And they like— I was really surprised to hear that some of the FAANG companies, still a highly manual process. So yeah, definitely, we got to be making sure that it can be ranked, although it's much more important that a human is going to respond well to your resume.

I would think FAANG is interesting because it's like everyone wants to go, like everyone wants to work there. So like there's probably no short of candidates who wants to work at FAANG, right?

Yeah, yeah, absolutely. And even I've seen that, um, in recent years, some companies, like some highly desirable companies like Apple, have completely stopped posting their jobs on LinkedIn because they just get too many applicants. So if you want to work at Apple, look at their careers page, guys. Okay, next question: can formatting hurt you? Yes. Yes, it can. Because like, oh, I hate— and I love Canva, but I hate the Canva resume. So why? Because it looks pretty. Maybe it's good if you are going to like hand it to a person. So you know that the human being is, is going to be reviewing this. But what happens with the Canva resume is that it is really hard to parse because Canva is not— it's not a program that is optimized for text processing. So you can add text to documents in Canva. Probably almost every document in Canva probably does have some text on it. Um, but because of the way that that text is arranged on the PDF, it makes it really difficult for, um, it makes it really difficult for some systems to parse that. So sometimes, you know, you won't get ranked at all if it can't parse it. So I would say, you know, keep it clean, keep it simple. A bunch of graphics and colors generally don't help you at all with the ATS system. So keep it simple, guys.

Um, as I— at least this is breaking news for me. Let's talk about this really quickly. Can we see this? OpenAI announces an AI-powered hiring platform to take on LinkedIn.

What?

Oh, what is— what's What is that? This is freaking— I'm just not—

I have not seen that.

Okay, like, what, what if we—

from today?

Yeah, what do we think about this?

Honestly, I think, uh, that makes sense because, I mean, you guys are also frustrated, right? The companies are frustrated because they're getting a bunch of lies. The, uh, the job seekers are all frustrated because they're spending all this time on sending out the applications. I mean, before, if you were getting like 40% return rate on, on your resumes that you're sending out today, you're getting 4%. Like if you send out 100 cold applications, it is entirely par for the course to get 4 offers to interview or to move forward in the process. So if you've got this kind of return rate, don't get down on yourself. That is the world that we live in today. So wouldn't it be great if we just lived in a world where a human would have a conversation with an AI once, Maybe occasionally answer some questions. And then the company or all the companies would have access to that information. And then the AI would just be like, I think you guys should talk. I think you guys should talk. I think you guys should talk. I think that makes a lot of sense.

And that'll probably remove a lot of the scams. Listen, LinkedIn has had a lot of scams, recruiter scams, like, yeah, a lot, and it's been pretty ridiculous. Pretty ridiculous. Pretty ridiculous. Um, so I'm excited actually. Yeah. I'm excited about this breaking news. That was not part of the— that was not part of the, uh, the agenda. I just saw it pop up on, um, my thing there. Okay, um, let's see what's we got. Is there any way to hack Or beat the ATS?

You know, I feel like these, you know, these TikToks and these YouTube Shorts and stuff come up all the time, like, just do this and you'll hack the ATS. The ATS isn't the thing that you can really hack. It's like, just send a good resume, be honest, align yourself with the job, cross your fingers and pray.

Um, hold on. Or also do what Kate does and, um, you know, actually talk to people on LinkedIn and, you know, get, get interviews straight from LinkedIn, straight from talking to the, to the, uh, um, you know, actually I saw something. Let me— I think I saw— I don't know if it was here. Someone asked about like, you know, scared to like network and talk to people, um, on LinkedIn, whatever. I mean, listen, for those who are introverts, LinkedIn and the internet is our playground. Okay, we are in a comfortable environment, i.e., our room or office, right? So this is our playground. Like, I feel like in-person networking and things like that is super scary. I, like, I'm personally an introvert. Like, I feel like introverts have the advantage if you really dig into it. LinkedIn and just online stuff should be your advantage over extroverts. So please hone in on that. And let's, let's give it up for Kate. She's got another interview. Um, she just got an interview today for Monday. Listen, listen, hey, everyone give it up for Kate. All right, she is one of my students and she's been just kicking butt. Okay.

Because, because why? Because Kate talks to a human. Kate sends messages on LinkedIn. And this is what we need to be doing to cut through the noise.

Absolutely.

Kudos, Kate.

Uh, yeah, shout out to JC saying good luck. All right, thanks JC for the, um, um, hold on. Troy found an interesting article from the Register outlining how AI implemented in hiring may show bias. Yes, absolutely, there's definitely bias. Um, I feel like that's definitely something I've seen that multiple times though. I mean, that's definitely way higher up above my pay grade, but there are literal, like, people who really talk about the ethics, like AI ethics and bias and things like that. There are folks who are, like, very hard-nosed about that. So anyone who's, like, interested about that, there's a whole, like, AI ethics— um, um, let's see. Yeah. If y'all wanna take a look at that. Yeah. And that looks like it's recent. Uh, 3rd. Yeah. Okay. That's good. Um, I can't copy and paste that.

I can send it to you later. I just did.

All right. Perfection. Um, all right, let's, um, all right, let's see if we can have like any final words or also let's talk about like, you know, Emily, I mean, listen folks, they, they want to know more about you. They want to stay connected to your insights. Um, so talk to me about this new newsletter, actually.

Yes, guys. So I am super excited about my newsletter. I just started it. Um, you've got the QR code right there. So I'm actually gonna— I'm gonna drop a link here to issue 1. So what I'm doing with this newsletter is I am compiling Oh, I, for some reason, I cannot, I can't, I don't know why, but I can't, I can't post a link.

Oh, send it to me. I'll post it.

Let's see if I can send it in here. I just sent it to you in the studio chat. Um, so this is the direct link to, um, the first issue. And so what I'm doing here is I'm doing a couple of different things. So number one, tips about job search. Tips and conversation around tech and AI in hiring. And then I'll be doing jobs. So, and what I mean by jobs is like featuring particular roles that are cool for a particular reason. And I just saw I posted this one yesterday. It goes so fast, guys, that this job is already down, but it's a really cool job of— for an AI specialist in healthcare. I know it's not super data related, but it was like super cool. Based in San Diego, looking for somebody who's got a background in healthcare and the compensation's really good, up to $187K. So I'm just kind of calling that out and seeing like kind of the unicorn jobs that I'm finding online throughout the week. So you keep your eyes posted, keep your eyes posted, keep your, just stay, stay posted. Is that what we say? Stay posted for, for data jobs to be popping up there at some point. But yeah, so that's basically what I'm doing. That also been taking a foray into the social media, doing daily tips on like LinkedIn, TikTok, and Instagram. So that's all new for me. So if you're interested in getting some daily tips around like the super, like the most typical questions that I get from my job seekers on a daily, weekly, monthly, yearly basis, feel free to tune in there.

Yeah. Oh yeah. And, uh, we know, at least my students have known, um, you know, you know, Emily has way more sauce that she's, you know, holding back. But like, some of my students are— they, they've, they've, they've been loving the— she's, she's— listen, she is— she knows what she's talking about.

It can get a little spicy in the Data in Motion chat sometimes.

Well, you know what, listen, it's— I mean, It's, it's, it's cool. It's, it's a, it's a great— it's the best community on the planet, best data community on the planet. But, um, we, you know, we're talking about folks who, you know, barely GPT savvy, and you've taken them to like creating custom GPTs for like their job search and things like that. You've helped— yeah, you know, Inner Shell already getting like, what, she got like 3 interviews or something?

Yeah.

That's like 2 weeks or something. So yeah, you're definitely Emily knows what those are stuff, so y'all gotta subscribe to that newsletter like legit.

Thank you so much.

Subscribe to the newsletter. Um, you're on, so you're on TikTok, you're on LinkedIn, and you're on Instagram. That is a lot. You're everywhere all at once. Y'all gotta, I know y'all are on there. So listen, you know, I'm, listen, I see the shorts. Um, I saw this YouTube short actually about like how to like make, make really good cabbage. But listen, that's not I mean, yeah, but what would be better if, if my timeline was filled with Emily, you know, job searching tips, you know, and then not the Dubai chocolates and the, you know, these, these fads? This is, this is, this is the good stuff that you guys want your TikTok feeds on or your Instagram feed on. So definitely subscribe and follow Emily on all platforms.

So Emily Talks Tech Jobs, guys. Find me.

Okay.

Um, all right, I think I don't have that name yet, but hopefully I'll change it soon.

Okay. Um, so just like before, you guys, um, what, uh, post in the chat, like, what, what, what next do you guys want us to talk next? Um, we are— the dream team will assemble and, and discuss what, what you guys say. What, what, what, what should we talk about next? What's on your minds? Okay, we are in We are heading into the 4th quarter. We're not quite in the 4th quarter. Are we in the 4th quarter of, uh, 2025?

Not yet. Next month.

Okay, so we're heading into the 4th quarter 2025 soon. So if you want a job this year, you pretty much— your goal is should pretty much have an offer by Thanksgiving. So, right, so what, what would you like us to cover in these live webinars between now you know, the next, you know, through that to the holidays to really get you, really get you going, right? We are— this is September, okay? Cover letters, when and how to use them. I say throw them away, but Emily, you probably have some.

That depends.

Okay, cover letters. We can probably— I don't want to speak no 60 minutes over cover letters. We could probably add that on in there.

Yeah, that can be a section.

What else y'all got? Let's see. Dream team.

Have we done interviews?

I don't think so. I don't think we've talked interviews. All right, let's— okay, we can do interviews. Cover letters, where to throw them away.

Uh-huh.

Uh, what else, you guys? Uh, yeah, interviews. What questions to ask at the end? Um, okay, how to answer, um, how to answer tell me about yourself.

Yeah, there's a ton of stuff. I think an hour might be short for interviews, but Kate, I think we'll be talking about interviews next week, so See you there.

Yeah, yeah, yeah, Kate. Y'all, yeah, you know, okay. Interviews. I'm just gonna put interviews. But okay, come on, you guys. What y'all got? About 60. How to navigate an offer. Yep, Kate, because you'll be navigating an offer pretty soon. Okay.

Yes, you will.

How to navigate an offer. How to negotiate. Navigate. How to negotiate. I know some people, and mostly females, say that they will not negotiate, which is a no-no,

right? Absolutely.

How to

negotiate. Oh, hi, Danielle!

I knew that— I knew the Dem folks was going to be here. I, I knew at the very least the Dem folks was going to be here. Um, Okay, so we got— I wrote it, I don't know why I wrote the nail. So, um, pivoting with no experience. Okay,

that's good, good topics.

What else? What else you guys got? Listen, I see— I know there's at least 30 people here. Like, come on, I should see like 30. I should see 30 ideas. Like, come on, what is it? What do you guys want to know? Okay.

Everybody's good.

Okay, are you sure? All right. All right,

hey, if you come up with something, guys, drop either me or Kedisha a line in, uh, uh, on LinkedIn. Just send us a message if there's something you want to talk about.

Yes, connect with Emily and, and, uh, share. Um, okay, I guess that— I guess that's probably closing in on the night. Um, I hope you guys enjoyed it. Um, and hopefully, uh, we will be fully healthy next time and have our third. Okay, we were one down. Hopefully we're at— we will be at full strength, uh, next time. Um, yes, you guys, uh, lastly, make sure you guys follow, you know, connect and follow Emily on LinkedIn. Okay, she has her favorite color is purple. Um, she has a lot of stuff. Look at that, she's, she's spoken at events. So listen, they don't just hire— they don't just invite anybody to speak, right? So this is a big deal.

Okay, these are fair— in fairness, these are all from the one event that I had a person taking photos of me. I have spoken

at other events.

I don't know if you can tell that that's all the same background.

You should have wore like 3 shirts.

And just like change mid-session. I'll think about that for next time.

Yeah. Um, uh, actually, this, this gives me a thought. Honestly, if anyone wanted to like make— like do something like this, they could just go to like an empty theater and have like a light and just, just You know, pretend, put a mic in their hands, just look and just have someone take a photo, and then no one would know,

right? Absolutely.

No, there could have been zero people. We don't know.

I was standing in a university auditorium. There were probably 150 people in the crowd when I gave that talk.

Okay, okay, we'll take Emily at her word for here because we trust Emily. But hey,

I called out that they were all from the same chat, so.

Okay. Oh, Nancy has a good one. How to deal with ageism. Actually, that's a good one.

That is a good one.

Yeah, Kate, they sell green screens on Amazon. Absolutely.

You might— you never know, I might have that behind me right now.

Oh yeah, that's probably not plants behind you, right? Okay, okay, okay. Um, all

right,

all right, you guys. Hope you guys have a great night.

All right, bye-bye. Thanks, guys. Bye, see you next time.