The tech industry has seen a significant change in the skills, qualifications, and titles listed in job postings over the past few years. What does that mean for companies - and for the candidates themselves?
On this week’s episode of Dev Interrupted, we talk to Maryam Jahanshahi co-founder and Head of R&D at Datapeople, who breaks down the biggest hiring trends in tech from title inflation to salary transparency and the skyrocketing costs of recruitment.
Maryam also discusses how the storytelling skills she picked up from data analysis have improved her abilities as a founder.
- (2:05) Introductions
- (6:13) Title inflation trend
- (11:00) Hiring trends: salary transparency
- (16:11) Bringing data to the recruiting process
- (21:55) How Datapeople is leveraging ML
- (27:30) AI job trends
- (31:30) The importance of storytelling
- (35:42) Maryam's advice for founders
Conor Bronsdon: We are back on Dev Interrupted, I'm your host, Conor Bronsdon, and we're live from New York with another incredible guest. Welcome to the show, Miriam Jahanshahi.
Maryam Jahanshahi: Thanks, Conor. I'm excited to be here
Conor Bronsdon: And I really love that you're here because we don't talk to data scientists that much, and you are not only the head of R&D and a data scientists at Datapeople, you are also a co-founder of that company?
Maryam Jahanshahi: I am a co-founder. I also work very strongly with engineers and so like I'm always up in their code and in their pull requests and. All the fun side of things. I guess that's one of the things when you get to be a technical co-founder, you have to run the gamut of all the different things that you do.
Conor Bronsdon: So yeah, it was fun talking to you as we were getting set up. And you mentioned you had this opposite journey where you really dove into the data side that were becoming like this strong data scientist and then you realized you wanted to add these data engineering skills to the table.
Maryam Jahanshahi: Yeah it was a, it's an unusual experience. I think part of the reason why I had to do it was I. Figure out the systems that we needed to analyze data to get a data-driven product. And so my role now is it is such a weird mishmash. I was talking to my co-founder about it the other day.
I'm neither like, Nor do I run engineering, nor do I run like the data side of things. But it's almost technical product manager. You're the huge, between the two of them, it's like a weird mix of many different things. Yeah. And so we're realizing that, that requires a certain level of skills and different types of agility and so it was easier for me to actually write my data pipelines.
Then have then write the spec to give it to the engineers to do it's yeah, this isn't so bad. So we realized very early on, like with these systems you, I think increasingly as the tools as our data becomes bigger, we're gonna have new classes of product managers, including like data informed, product management.
I'm sure things like chat G P T are bringing that to the fore. But it's not just that, it's anything that. Adds a level of analytics to your dashboards and things like that. Like you, you want someone who has a business interest, but also is able to run the sequel query to figure out what the hell went wrong with that dashboard.
And so it's an interesting transition that. I don't know whether I'm crazy for making it, but it's what the organization needs. So it ends up being a fun,
Conor Bronsdon: I think it makes a lot of sense, right? If you're a data scientist today, you want to add that skillset so you can better interface with these tools that are able to extend and, leverage your work.
Maryam Jahanshahi: Correct. And it's been really like, so I told myself Python mostly to get a sense of how do we like. Very reproducible processes to understand data. And then that's been a gateway drug, international language processing, which obviously at data people, we take career documents, whether it's resumes or job descriptions and take and extract really important structured data so we can run analyses and understand the impact of things.
so that's been my kind of gateway drug into things. But I sometimes read a little bit of PHP because that's what I'll like, love. Monolith is written in. And so it ends up being, once one of them, you start getting a sense of the, you start seeing the patterns. Yeah. You start seeing patterns. I did not ever imagine myself as someone who could code or code competently, but It's a, you find your ways. Cause I think when you have a question that you wanna answer and there aren't any other ways of addressing that question, you are like, okay. Let's have at it with all these different tools and it's been a really great system. So
Conor Bronsdon: Is that a mindset that shifted for you over your time at Data People?
It's now been, what, seven years since you founded the company?
Maryam Jahanshahi: It's been seven years. And finding the right tool and deciding on the architecture for those tools has been really important. I'm now starting to get a better sense of how systems are put. And going end to end from the like germ of an idea that you have to like building out, we're building out our second product right now and that's exciting, been an interesting topic because the things that fuel the first product might not work with the second product.
Yeah. And so just splitting off, infrastructure into a very different systems just needs to happen. So that part of it is something that honestly, a couple of years ago, if someone had told me, I'd have to. Run things on aws, I'd just be like, no, thank you. You guys keep it. I'm gonna stay with my lovely statistics.
But you get excited cuz you're like, this can change the nature of how we do recruiting. It helps teams do things in ways that are just so un, terribly manual that it just feels like a. I can imagine how engineers really enjoy that process cuz you set up a system and you let it go and you see what people do with it.
Yeah. And it's, that's amazing.
Conor Bronsdon: So I'm very curious about what you're seeing in that data. Obviously you now have this data engineering role where you're bridging the gap between data science and engineering. Yeah. What are the trends that you've seen in your time at Data people and what are some of the big takeaways?
Maryam Jahanshahi: One of the things that's been really, so I hate to be the scientist who said, oh, I told you guys but one of the things that's been very exciting in the last year is that, we've been talking about things like title inflation for a long time. So an inflated title is when the job description doesn't match the title.
You have principal engineers who have job descriptions that are only asking for two years worth of experience.
Conor Bronsdon: Principal engineers cover your ears.
Maryam Jahanshahi: I hope that they've all got more than two years worth of experience, but, we've seen that trend. We, we were annotating it, noticing it.
And in the last year it's gone through crazy uptick. That's tied to the labor market. It's tied to companies trying to. Lure and attract candidates because it's really hard to hire in tech. So that's been something nice to see. I know I had a conference talk about it like five years ago or something where I was like, this is a thing.
And people are like, what are you talking about? And now I'm so excited when I get look at the data, it's a tweet. Some people are like, reelecting those tweets and we're very excited. So it's actually that part of it's been really. We're not the first to have thought of title inflation.
Obviously, it's not our term, but it is something that we've been studying because we know that it has impacts and now we have the data to show that look, it doesn't matter what type of organization you are, whether you're a tech or a non-tech company, you've still got the same problem. Where at some point I like to think of that there is no free lunch, right?
Like you can give someone an inflated title. If you don't give them the pay that goes with it or the responsibilities that go with it, they will eventually lead your company or they'll go somewhere where they will get that. that's been the lesson is being transparent and clear with candidates with your employees is really important to having a well functioning organization.
And we just try and write software that helps people. Get there to help humans communicate. Yeah. Which is wild.
Conor Bronsdon: It's amazing how challenging that can be, right?
Maryam Jahanshahi: One of the things we think a lot about is like people don't love confrontation. Obviously when you're collaborating with someone, having those hard conversations can be really difficult and it can be really easy to be like, here's a system and it's making us.
Do this thing and we have to abide by it. It's much easier to blame a system than to blame the fact that you two are going into a system, into a conversation with very different intentions. And so that alignment that happens in hiring processes really has to happen very early on. But it's the same thing when you're working as well.
Like you need to be aligned with your manager about where you're going. You might have slightly different, But if you are over here and managers over there, we've got, you've gotta somehow get together. so basically, yeah, it's not fun having systems that like force people to do things. It's much better to like, facilitate that conversation.
Yeah. And to come to a compromise. But yeah we deal with those systems all the time.
Conor Bronsdon: I'm curious to dive a bit more into the title inflation piece. Have you seen any impacts from the recent waves of tech layoffs? A bit of, deflation of that title Bob Berth at still continuing at Pace.
Maryam Jahanshahi: We haven't yet seen the effects of that on the market Too early. Yeah, it's too early. I think it's gonna be really interesting. We saw, so in certain cases, we saw historically that deflated titles were really attractive to people of certain backgrounds. Like especially if you don't. For instance, an engineering degree, like being called a junior software engineer was like quite attractive to some folks that people like wouldn't think of.
And it might actually be helpful for people's efforts to like, interesting. Try both. Especially if people are trying to ensure that they have a representative candidate polls and things like that. We haven't yet seen it. I'm curious to see how it's gonna play out anecdotally in our.
We're hiring a VP of End right now, which is very exciting. And the kinds of candidates that we're seeing in the pipeline, very senior SVPs at different organizations we're not things we've seen for many years. Yeah. And I'm sure we not the only ones, but this is a weird market right now to be in.
Conor Bronsdon: So we've had some similar experiences, I'll say in the recruitment I've been involved in. Yeah. So I'm very curious to see how that our kind of like anecdotal observations Yeah. Bear out in the data over that time.
Maryam Jahanshahi: Correct. And I think like it's somewhat also restricted to the us we've been tracking labor market developments.
we do because obviously it's related to our product in different locations and Europe has seeing less of it. But Europe is also now seeing what the US has seen for the last year, which was labor market tightness. So it's gonna be interesting, especially companies, big companies that have like multiple places, how are they gonna distribute work?
if you've got like more candidates in one place on less than others, The US costs more. So it's
Conor Bronsdon: Outside of title inflation, are you seeing any other major trends in the data?
Maryam Jahanshahi: We're seeing quite a few. our biggest trend that we're seeing right now is job descriptions are becoming incredibly.
Which is fascinating from a natural language processing search process cuz you know, with algorithms like TF I D F or other forms of normalizing rate, if you have a very long document that's got a lot of non-specific language versus a very short document that's quite tight, which one's gonna do well on search, which is a lot of companies can talk about their search things, but basically comes down to some level of normalization overlay.
So we're seeing that. And a lot of companies talking about their values and their job descriptions, like coming back to it's, there's a big push about culture and values. That's happening. I don't know how that's gonna pan out. We have these discussions a lot and some of the stuff is coming out because of pay transparency.
So in Washington State the regulations require you to disclose exactly how many days of leave you. Or any non-comp benefits that are like meaningful. And so that's changing the nature of job descriptions. What I'm super curious about figuring out is what's happening to candidate pools and things like that.
People are talking a lot about you'll have multiple locations and things like that, but that's a fascinat, that's the big trend that I'm curious about. It's not the inclusion of salary, but how does like a lot of actually job seekers. I don't believe the salary that's in the job description.
Which is interesting. That's intriguing. Or is the salary above or below the media and so is, does, can salary act as an attractant? Do you trust that as a signal because there's This a new era of transparency. I think that's happening in job description.
Conor Bronsdon: So fascinating.
I'll say I'm a Washington State local. Yes. And I work familiar. Yeah. So you're aware. But I see it when, I'm getting the LinkedIn sponsored post, so who apply to this job. It's been really intriguing to see that trend change where suddenly now there's a lot more upfront information.
I'm also seeing, I'll say like very broad ranges.
Maryam Jahanshahi: Oh yeah 90 to 900,000. Yes. And you're like, how? So I've spoken to HR leaders at organizations where, Like they're tech companies, so they have this sort of thing and they're like, they're very worried about being litigated. And so they're like, if we give them that, the possible possibility of Ranger based on historics including.
A lot of other information, then we won't get sued and they don't wanna get sued. So they're very afraid of that.
Conor Bronsdon: It's understandable. Washington State Attorney General Bob Ferguson is very willing to enforce regulations.
Maryam Jahanshahi: But on the other side of things, you're like, you're, you are not in the spirit of law.
And I think in Oregon and in New York, they've been I think you see the ranges are much narrower because they're. It's in your best estimate. So if you hire someone at a different level, a slightly higher level, you won't get penalized cuz it was your best effort and you're like, it was a L six versus an L seven.
But in Washington state it's not, they haven't been explicit and they haven't gone through that.
Conor Bronsdon: Probably some regulatory clarity they need to bring to that.
Maryam Jahanshahi: They do. And I think you'll see that pan out in the next year and hopefully that will add clarity, but it's amazing. one of my teammates, she's she used to be a teacher for a long time.
She's a linguist on our team and she's like this whole thing we have complete clarity in every other profession. She's her, parents sort of work In warehouses and production roles and like salary transparency has been part of that industry for a long time as well.
Yeah. She knew what her colleagues were making at her school as well, and she's you knew what you needed to do to get to that next stage. So she was like, this is wild. That there's a lot of, there's so much angst because it's like, it's fine. It's a big change, but it hasn't fundamentally changed other industries that much.
Like the things that people were afraid. Haven't yet happened. So yeah. That's been an interesting intersection where we've seen like things change in the last year that like I never thought I was just amazed when it got signed in California cuz I was like, that's gonna change things for a lot of big tech companies.
Yeah. All of a sudden, and they also have to report to the government what their gender statistics are in terms of say, salary and like levels and things like that. Which is a, which is the other part. Requirement that I don't think anyone's yet dealt with really talking about too much. Yeah.
Yeah. But people have been doing that in Europe for years, so it'll happen. So it'll happen.
Conor Bronsdon: This is fascinating.
Maryam Jahanshahi: Sorry, I'm like, I get super geeky and excited about this.
Conor Bronsdon: No, I wanna know more trends. I'm like, what else is happening?
Maryam Jahanshahi: What else is happening? So we have titles we have
Conor Bronsdon: For folks listening. I've gone entirely off script. We had an outline. We're talking about these things. I'm like, no, this is so fascinating.
Maryam Jahanshahi: What else have we been thinking about recently? I'm just trying to think of stuff that I've talked to my cus our customers about, because we have these conversations with customers to talk about what's happening in their stack, how are they changing?
Cuz these are recruiting teams. At many companies, they've gone. Significant layoffs. Because if they're not hiring challenging economic times, they're not gonna be dealing with those with outside of it.
So I think the other thing that's really interesting in the, our field that hasn't yet happened everywhere else, and it's I think of recruiting as where marketing was like 15 years ago where It's wild to me that we spend the US I think spends 17 billion on executive search every year. That's the size of that market where it's like a head hunter or reaching out to someone. And it's not just like senior level roles where that's happening. We're seeing that's happened in junior level software engineer roles.
Totally. The cost of getting interns is sometimes more than the amount that you'll pay the interns in terms of, Not acquisition, but you'll Yeah. Advertise in places and I think what I think is a really exciting trend is unfortunately caused by the economic situation. We need to people need to be able to talk about efficiencies in the process.
And that's where their focus is. And so that's causing recruiting to be like, what are the costs of all of our channels and which ones are actually doing well for us? it's becoming a lot more data driven than it's been in the past. And so our, what I love about recruiters is they're like, our hiring managers are engineers.
They want us only to advertise on like Stack Overflow or GitHub jobs, but we don't get any applicants from there. They've been like, we wanna know about niche job boards, cuz we wanna go back to the people and say, this is the evidence, this is a cost. Like we could pay a candidate at a hundred dollars per candidate and we'd still, it'd be cheaper than advertising on those platforms.
And that's wild to me that you could pay to and get so little and have no visibility. You start applying
Conor Bronsdon: more, what am I doing? Yeah,
Maryam Jahanshahi: I know I'm like, if you just put high Craigslist ads for applications, it might actually be cheaper. So I mean I think there's a reckoning cuz it's this whole field has gotta go through that.
That sense of what's the cost of, not a cost of a candidate, but like how do we get to more candidates more efficiently?
Conor Bronsdon: Candidate acquisition costs, we can just say
Maryam Jahanshahi: CAC again, instead of cost, we can say CAC again. Yeah. And it's what's their lifetime value? Yeah. We haven't gotten to that level of sophistication.
Yeah. But I think it's, I think that's a, it's an intuitive step. I think one thing that I am always amazed by, Even though marketing has had this idea for a long time is that their stacks are as bloated as everyone else's. Like it's like I've, I hear of so many point solutions, do this thing to this tiny little step, but they don't take you the full way around.
Like we, we, our marketing stack is as bloated as anyone else's. And that's an area where I think. Recruiters can be a little bit, or recruiting teams can be a little bit more efficient. The other thing that's actually really interesting, that's, this is the other trend that I think is that impacts candidates less, but it's actually fascinating.
So business systems, if anyone's ever dealt with an e r p, an SAP or workday or whatever else, I would call them user hostile systems, like really, frankly. And they. Horrible to navigate. And they don't invite collaboration, right? Like you have your Workday person to make Workday a little bit more pleasant to deal with.
And you, it's just amazing to me that you hire someone in your company to create this like layer in the system that is just, I don't know if you've had experiences with, we hire Salesforce engineers exactly. Salesforce engineers, like HubSpot administrators it's like this whole.
For me, the idea that those software softwares need someone in-house, cuz this tells you a little bit about I come from academia, we don't normally everything is self-service there. So the fact that you have in-house people that are experts in this one thing is amazing to me. And that we call it still a service cuz I'm like, it's a bit of both.
We have to
Conor Bronsdon: hire someone to manage the service. Yeah. And maintain it
Maryam Jahanshahi: okay, at scale Sure. Sure. But it's like a, it's a tense thing. So these user hostile. And you generally don't want everyone in them, right? You wanna train a group of people who can deal with this user hostile system so that your hiring managers don't have to touch it.
They can have the experience for the candidate. And what we're seeing recently is that this is a collaborative process and the more that we make these systems collaborative and able to be interacted with together, the better that like deals with that alignment. That you don't have someone putting some set of things into the system where the other person is like, you get to an office stage of the candidate and the hiring manager's who the hell is this person?
What are you doing? Based on what? Bringing them, having systems of collaboration. I think Google Docs did an amazing thing for collab and no question Google. Like that whole industry's done an amazing thing for collabo. We have that in any of those like, and can you imagine doing that in Workday or Salesforce or any of these systems?
that's where I think the next generation of like business software has to come. Whether that is within Salesforce as like an experience layer or whether it's like, Hey, I'm gonna burn Salesforce down and build you this new thing that allows you to collaborate and interact in a way that's like part of the system will be different.
So I think we're seeing that trend in terms. For us we integrate with a lot of application tracking systems, so things like Workday, greenhouse Lever. For those of you who are in startup land, And like they're getting a little bit, they're better than what the previous generation were, but I think there's another generation that will have a much more consumer focus to that business software.
And I think bringing people into that process. Gonna make those processes better. Rather than being like, here, recruiter, you deal with your little sandpit and I'll deal with mine and then we'll collaborate over Outlook or Google meets or whatever, as in whatever your messaging system is.
Conor Bronsdon: Totally. So how are you applying machine learning to this massive data set you have?
Because I'm super curious to see what insights that's generating and how it's fueling your product innovation.
Maryam Jahanshahi: So we. Language models in a couple of different ways. One is to extract entities. We've been training that, for instance, to pull out salaries from job descriptions. Part of that is because we wanna tell companies, our customers if they're not compliant with that legislation, then that's been actually really fascinating.
Conor Bronsdon: Oh, that's an awesome tool to have. Yeah.
Maryam Jahanshahi: Yeah. Okay. But we've been doing that for ever since the salary legislation came out. We were like, yep, we should be capturing this and trying to surface this up. And that's been really an interesting experie. The other area where we use machine learning is, we extract a lot of features.
Our features are not unsupervised. So we do have some supervision cuz we think that things like tidal inflation are really subtle things that like, make sense to a human that are hard to do that. But what we then do is throw it all into a model and say, okay, what are the things that are like most correlating with success in this process?
What are trends that we're seeing, which I think has been a fascinating side of it. So a really good example is we published a tech hiring report last year at the start of last year, talking about how skills and qualifications and even titles in different tech jobs have changed over the last couple of years.
And like how we're seeing specializations develop in certain types of roles. Companies are less likely to talk about, certainly more startups are less likely to talk about software engineer. They'll be talking you out a front end engineer or ujs engineer versus like a backend engineer and being specific about the subtypes.
That's definitely happening. So like we're seeing, I guess I wouldn't call it maturation, but it does feel like it. I think in biology terms, so like you start with an embryo, you end up with a very okay, put your hand right, which is like full of very differentiated cells. And we're getting to that level in some fields within tech where we've got that level of specificity and others are still nascent, they're still growing.
More companies are adopting things like analytics engineers than they used to be. It was a very startup thing to. But I think now people are less likely to be bi engineers, more likely to be analytics engineers. They're different jobs actually. But it's been, it's interesting to see that rise.
What was the sort of subset that we saw a couple of years ago, very handful of companies had where it's now you don't have an analytics engineer. What are you doing? Like of course you need this person.
Conor Bronsdon: Who are you gonna do an update to that report this year?
Maryam Jahanshahi: Yeah, I was actually thinking of doing it.
It was such, it was actually a lot of fun to generate. And it was funny cuz we did do an update at one point a small one for a Business Insider article and what was amazing was you, whenever you haven't touched infrastructure in ages you think you are like, It could take five hours.
It could take five weeks. Yes. I dunno which of these it will be. It was five hours. We have a great engineer. That's great. And it ran really well and it didn't break and I was just like, I don't know how well we engineered this, but he did a phenomenal job. So yeah, we will, because we're like, yep, we've got a whole lot more data to look at.
We specifically focus on like companies not. Nonprofits and like education and defense organizations, which are just their own, like they need their own rapport. Yeah. I dunno how much they change as much as companies do, but it's been something that we've been fascinated by. But also to look at the difference between tech and non-tech.
One of the things that I was amazed by, I just ran this report the other day, 50% of so tech companies, so you know, your Microsoft's. Whatever they're called now. They're not called FANG anymore. What are they called? Oh, I don't know. Matt, Batman, whatever. Those companies don't account for that much.
Like they do account for a lot of jobs, but not as many as you would think. And a lot of the hiring that's still going on is in non-tech companies, startups, but also like big companies that are. Not where you would imagine
Conor Bronsdon: so like a capital one that wouldn't be defined probably as a tech company, but definitely not.
It's hiring a lot of engineers maybe. Yeah,
Maryam Jahanshahi: exactly. They're like, no, exactly. It's like the people who like might be tech might be 10% of their jobs, but they're actually 50% of the US economy's tech jobs and so they are underrepresented in our mind space because totally everyone thinks of tech companies and I think.
As someone who's worked in a company that's recruited engineers and you're like so grateful to suddenly have the ability to hire engineers and every one of them is amazing. It can be really fun to work in those companies because you suddenly you've, you are like, you can be a huge pacesetter.
You could do things for those, for PE teens that like couldn't even imagine that it could be done. And because they've had such a tight labor market, it's been so difficult for many companies to recruit and. It can be really impactful work. And so I think that's been an interesting, switch.
And those companies are hiring, they're hiring now. They don't seem as perturbed by layoffs. They didn't overhire or stockpile people or do all of the anti-competitive things that, we know that some tech companies Yeah. I say this as someone who's just yeah, it was difficult for us to hire.
I'm sure it was difficult for you as well.
Conor Bronsdon: One, I'll say whenever you get that report done and when it's published, we would love to link the show now. Hundred percent. I'd be fascinating. I'd love to keep diving into that machine learning AI access because I know, we've all seen the trends.
I'm sure it's so showing up in the job postings too, of AI engineers, how are you leveraging ai? What are we doing next? How are you seeing AI show up in, both your product Yeah. And how you're leveraging. Or plan to, and then also in job trends.
Maryam Jahanshahi: So I personally struggle with the blank page problem when I'm writing anything I I find it so much easier to have started even with a very crappy draft of something that I don't wanna write. I agree. Yeah. But job descriptions are the one place where I think I often go in being like, these are the three core skills and the, and probably the title.
Let me research, figure out what's similar. And I've had to do this actually. Last week because I was hiring a new position. I was like, what do other companies call it? And things like that. So we haven't found the need for those sorts of technologies or we haven't found them to be as helpful because part of what you're trying to, what we've seen when we've applied them, we've experimented for sure is that you get the average.
The average might sometimes be helpful for you in terms of that's good, but most of the companies that work with us, they're like, I don't wanna be average. I wanna be in the top 10%. And so it's a very different sort of kettle fish. The other thing that we have to deal with in terms of job descriptions is there's a lot of template stuff that.
Your employer brand team wants to manage? and your own like recruiters wanna talk about, like for instance your the perks and benefits that you offer, which are really important for candidates. And so your contribution is so little it is literally a paragraph. So we don't have as much to do that, but I've used it certainly to generate training data, to see to act as adversarial networks to some of our systems. Cuz I've been curious how it. We use it to respond to questions that we would be wanting to ask someone in the recruiting process to see what would be the chat G p T response. And can I distinguish is my question a good one or a bad one?
Ah, I think it's got a lot of very interesting things there. I think other companies would do more in the sourcing side of things. So sourcing is when a recruiter or hiring manager reaches out to a can. They've done some experiments with that apparently are pretty successful.
Absolutely. In terms of getting a very specific response rate. But, I don't know if you watched the South B episode, but I'm like, south B literally wrote an episode with chat g p t about chat G pt. You haven't watched it yet. I know too. Oh, it's really funny. But it's it makes you wonder like how much humans are gonna just be the.
Process for distributing like work is the interface for Yeah. Yeah. It's like at a certain point you start doubting your humanity. So it's a really interesting sort of, oh, we can give
Conor Bronsdon: the simulation stuff if we need to, but I feel like I need a drink and another hour for
Maryam Jahanshahi: that.
And so yeah it's been one of those areas where we use it in very specific terms because we're dealing with hiring data. We need to make sure that as a data product, the suggestions that we're. Driven by data that we can interpret it that we can explain to someone why it happens and why it exists and why it's important.
So something like title inflation. And we also know that like we've gotta manage the tension with other stakeholders and like trying to make it so that like it's clear to them why that is. Cuz usually it's not the person who's using our system that's curious about it. It's like the person who's the next gener, like next one over.
So yeah, being the interface of collaboration and like education has been really interesting. It's something that I do not feel like I'm at all, as a startup founder, you suddenly are like, I have to do just whatever. Like I need to do, but I'm like, I'm not an educator. I don't, I teach, but I'm not a great teacher.
So there's a lot to be done there that I think is really interesting. Yeah. That
Conor Bronsdon: upskilling piece is huge for a lot of companies, particularly as you try to, get more efficient, as you mentioned. Yeah. How can you get more out of your current team if you're constrained in hiring racehorses something else.
Yeah. And I know that's a challenge for a lot of companies. I want to zero in on something you mentioned about being a founder and some of the skills you've developed. beyond, diving into data engineering Yeah. Early, like learning that side.
What are other skills that you've developed as a founder in the last seven years?
Maryam Jahanshahi: A skill that I'm working on developing is storytelling. And I think I'm able to tell stories, data, storytelling, but we've gotta tell the stories of our company a little bit. And I'm, it was one thing that we didn't appreciate as much when we were smaller because, we'd have, people would tell you you need a position.
And I'm like, I don't know what that means. What does that means? Sounds like it sounds like to me. And then I suddenly start understanding it, like the thing that you set up at the start constrains the decisions that you make, which is actually a really good thing. So there was a talk earlier today who was talking.
Saying no more than saying yes. And that's one of the things that when you've got that clarity of vision and you've said that this is what our company does and it's really good at it, and we're not gonna do these other things, that's really important. so that's one of the areas where I think from a storytelling perspective, I've gotta get better.
You're practicing on a podcast. This is great. I love Time and effort and it takes a lot to get there. I think the other thing that it relates to is defining what type of company we are, which I think is correlated to that, but it's also a little bit different.
Also it tells you what you can and can't do or Will and won do. And we're in this weird, bizarre place as a company, a series a company. We raise our. A few months ago, thankfully. Congratulations. Thank you.
We are in a good but bizarre place. We have customers pulling product out of us and they wanna pay us. They're like, we wanna switch over. That's great. It's great. Most companies wait until series B to do the second product because you need another, like the organizational cost of a second product is not something, it's not just that you develop it and you've gotta, you're like coding is the easy part of it.
It's the selling of it, it's the training all the teams,
Conor Bronsdon: it new persona, how does it get rolled out within our go-to-market motion? How are we marketing it? What's the story?
Maryam Jahanshahi: Yeah, what's the story exactly? But also who, who's gonna. Do we have the same salespeople working both products? Oh, totally.
Do you have them differently? Do we have different ICPs for the products? Is how's customer success gonna serve it? Correct. So it's do you spill your, like that's why people don't do it at early stages because it's like it splits your organization into and you don't feel like you've got enough scale to d develop.
So that's one of the areas where like we think a lot about, we are very fortunate to have customers who are just. We wanna develop within this way, and that there's been some, it's not like they've got 20 different ideas that they're all like different options. It's like there is a strength to that signal.
So that's, They're very fortunate, but I'm very worried as an organization, like how do we do this sustainably? Scary. Yeah. And I'm like, I was talking to a candidate the other day and he was like, what do you think is the biggest risk of geo organization? I'm like, this second product is the biggest, it's both the biggest opportunity cuz we are seeing a lot out of it.
And it's wild to me cuz I got an m MVP out and then we sold two customers, de novo not existing ones. And so I was. Biggest risk, but also biggest opportunity. Yeah. And we have to manage that balance. So as a founder, even though I'm very excited to see this product, I'm so excited to see like users keep going back into it and using it.
Which was the first time I'd seen it and I was like, I didn't wanna look at the data initially cuz I was like, it's episodic use case. No one will use it. And then you're like, they're coming back every week. This is exciting. Oh hey. So we're in a fortunate position, but it, we have to make big decisions sometimes.
What you wanna invest in and how, so
Conor Bronsdon: I'm excited to hear later, we'll have you back in a year or two about how that product design journey with these design partners goes and where you're at. But I think now is a great opportunity to dig into some of that advice for founders maybe who are in the seed or series A stage.
Yeah. You've been there, you've grown these skills, you've grown this company now to a successful Series B raise or going multi-product. What advice were you, did you have for founders or wouldbe founders who. Either just started to think about okay, I have an idea or I'm starting to raise, or I'm pre-product market fit.
And in particular I'm wondering about your lens as someone who has multiple co-founders.
Maryam Jahanshahi: So one of the things that we found, we built a product, we probably overbuilt it at the time cause no one would. So we've always been a little bit of a, the big kid. Kids table. It's been an interesting journey.
We don't come from conventional tech backgrounds. So we've always had to prove with data maybe too much data that we can do the thing that we're doing. Cuz none of us came from Stanford. We didn't go to m i t, like we don't have any of the credentials anyone should have and we're not young. So is every single bias is working gain.
So some maybe that was internalized as. So we built we built, we got customers. And what was surprising to us was there was such a breadth of customers that we could sell to. And I think that was an interesting and important lesson because a lot of our competitors right now sold only to tech companies.
And so if you have a product that goes like that has diversity of. It'll break the brains of your marketing and sales team, but in Yeah. Downturns like this, right? Where you are buttressed a little bit because a lot of our other companies in our space ended up having to lay off like half their teams.
Wow. We don't have that. We have some tech customers, but we don't have only tech customers. We have, it's just wild to me that we have customers that are like 17 people, startups and they are also companies that. 70,000 people, employees who've been around for hundreds of years. That's, that sort of set of things is wild to me.
So having that diversity has been really helpful going after that diversity, because I think a lot of companies right now in this particular financial crisis if you're too exposed to tech, you end up really exposed. And it. Existential For us it's just a matter of, okay, what was, we were hoping three x growth is now gonna be scaled back a little bit, but like it's still.
It's still a multiple of growth that we're aiming for. Which is different.
Conor Bronsdon: How do you land those first lighthouse customers in a new vertical? Let's say maybe you started with tech companies Yeah. And you're like, Hey I know I want to get into healthcare or final services, something like that.
How do you go out and get that first
Maryam Jahanshahi: lighthouse customer? So we did a terrible thing, which I wouldn't recommend, but,
Conor Bronsdon: So this is the opposite
Maryam Jahanshahi: of advice. This is clear opposite of advice. Yeah. But it can work. The warning. We. So we are now just building an outbound sales motion.
We were very much a strong inbound sales. Yeah. Company, which meant that we got who it opens you up. You don't have individual areas where we are seeing huge concentrations, but that gives you diversity. So we built a lot of collateral, whether that's like marketing collateral, like we were trying to get that in through market.
This is changing now because I think we have now, it's distracting our organization. If the sale, if our sales team, for instance, on one hand is dealing with a nonprofit in West Africa, which we have a customer, and then in the next thing is talking to a really big industrials company that like serves your food, like ConAgra, like it's all, it's they're dealing with fundamentally different problems.
And it's hard for them to get depth. And so that's been the thing that I wouldn't recommend, but it also did buttress us from this level of growth cuz it's very tempting to go after tech companies.
Conor Bronsdon: I think there are pros and cons there to discuss, right? Where it's like maybe if you lean into a certain vertical, you can grow a little quicker on something, but you create this rigidity and this weakness potentially when times are tough.
And so it's an interesting discussion to. What other learnings have you had as a founder that maybe are a little less common in your opinion, or are things that I think you think are really important to drive home?
Maryam Jahanshahi: the hardest thing to remind yourself is like the first few months when you have no customers and no one knocking down your door At the time, it feels like things aren't moving fast enough.
And it's like those were the critical times in which we actually defined our thought processes about what we think about our industry, how we think we should build product. We actually funny story, before we got funded from external vc, we applied to the NSFs the Small Business. Oh, small business administrations.
Yeah. So they have grants for, it's called America Seed Fund. Yep. And didn't win Mum. But those proposals was so helpful for aligning out to Oh, helped shape you. Yeah. And like I still look at them now and I'm like, they still reflect and we had to have debates about that because it's six pages and you have to get everything in there.
And we, it forced a level of alignment that I think we paid, like we got the dividends off for many years. Writing is a superpower I would like, I am terrible at writing, but I think that was instructive cuz we had to have debates about things that maybe weren't comfortable or the extent of things that we'll build but won't build.
And that forced those discussions. Don't necessarily go after the NF and throw as in, have those conversations. But I think having a very. Pitch proposal in terms of what you're writing is a superpower that every founder, I think, needs to develop, especially when you work in remote environments where you have to transfer a lot of information to people through written text. That. Was really helpful for us.
Conor Bronsdon: That distillation process.
Maryam Jahanshahi: Yeah, and just refining it. And I'm like, I remember at one point saying to my co-founders, I'm like, we should do that again. And they're like, are you nuts? We're too busy. And it's yeah, we go back into a cave and it's just us in a cave, but like now we have amazing teams and you wanna involve them in the process.
But part of what I love is that I can refer back to this and be like, look, we cut thought about this in these ways. And it's funny now when you look at those cuz you're like, oh, they're in some of the tech stuff that we were suggesting at the time, cuz it was like years and years ago. You're like, oh, that, that got solved.
Or it's still an intractable problem. Like matching resumes to job descriptions is a really hard problem. And we thought we had this great solution and maybe we do. But it was it was a really interesting kind of experience that I would recommend, whether that's for a VC pitch or. To share with other people, especially as early founders.
I think that was really helpful for us. Thank you for these insights, Maryam.
Conor Bronsdon: I've thoroughly enjoyed this conversation.
Maryam Jahanshahi: I had a lot of fun too. Thank you. Conor,
Conor Bronsdon: I'll say for anyone listening, if you love conversations like this with Maryam, Let us know on social media. We love to hear about the type of guests you want. I know we default to a lot of engineering leaders, but we also love these kind of deep dives with leaders here, maybe from a non-traditional for our show background.
And so we'd love to hear from you. Is this the type of thing you want to hear? And you'll see more of us on our CK at Dev Interrupted. Thank you so much, Maryam.
Maryam Jahanshahi: Thanks Conor.
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