Episode 10

Emily Loh on the Challenges of Hiring for Data Roles

TIM: So Emily, when it comes to hiring for data roles right now, what do you see as the biggest challenges in the market?

EMILY: So I think data has become quite a large field in the past. I would say two decades, give or take. I think one thing, of course, with the rise of AI is that. You really need to have a really great idea of what your data strategy is before you go to hire. I think one thing that I really struggled with at the beginning was of my leadership career was that. I thought, okay, I'm hiring a data scientist and data scientists can do it all, but that's really not the case, right? There's a lot of specialties. There are ones who are more academic leaning more on the MLAI side or, for a product, et cetera. So I think one of the biggest challenges is because there's such variability on the market. That goes both ways, right? Employers are all looking for different things. Employees are also looking for different things. And so when you go to hire, you really need to nail down your culture and the identity of your data team that you want to be running. before you go and hire. And then of course you need to calibrate all of that. And that includes seniority, leveling compensation that goes along with that. The expectations need to be pretty crystal clear from both sides. You want to make it attractive as possible to, draw the best talent that you need, but then you also need to have an eye for seeking out specific types of people and specific types of skill sets. I think that's a huge challenge. We just made a transition from data analytics to data science formally. And as part of this exercise, we've realized that. We may be we hold a different bar. I don't know whether it's higher or lower, but we hold a different bar to different companies. And so I, candidates are coming on saying, Hey, I want a certain level of seniority and we're thinking the role is really this, which is this level of this seniority. And so that has been a real big challenge. And I think that it goes across every data role, in the business or in a business. And yeah, just really Seeking out, the points that you really need to fulfill in a specific way, rather than blanket understand, wanting to hire for data roles in general.

TIM: and so having a very deliberate conscious approach that's well thought out ahead of time, I tend to notice, I don't know if you've seen this as well, that maybe companies Dive into hiring a bit too much. Like it's fine that once you're going, go as quickly as possible, but maybe it pays to have a bit more forethought and structure into the hiring process and do who you're looking for and why, how they're going to fit into the team, et cetera, and it sounds like you've taken a progressively more deliberate approach.

EMILY: No, for sure. It comes from a couple of mistakes that I've made in the past, at the beginning of my leadership career and coming from companies in which, I came from Uber, for example, and Coinbase was a little different but for Uber, it was Just growing, it was just like at the time I joined, I think it was 2016, 17, and it was 13, 000 people strong. And so the approach to hiring was really about, we just need people. And then you just get them and, you have a lot of talent, of course, but. There was not necessarily a role or a specific outcome that was attached to the hiring in and of itself. Whereas now, especially with the economy being what it is, of course, in crypto, which is what Moonpay is in, it's a tough industry. Things move really fast. You have down markets, which are very, often the crypto winter is very long as we say, and you really want to prepare yourself to make sure that you're creating resiliency within your team to weather all of those changes. And that cannot be done without exactly when you go to hire, really understand, do I need this person? What are they actually going to do? And is this person able to do those things? Otherwise, yeah, it can get really messy on both sides. The experience for someone who's hired as, for example, a data engineer or a data scientist as a generalist. And then it turns out that they're not used to the ways of working within your particular culture, or the things that they're working on are not really what they're interested in. And that can often be, a misalignment and just doesn't, lead to a good outcome for either party, which is not great.

TIM: Yep. I feel like if I reflect on the better and worse hiring processes I've seen, the better ones are the ones that are more fun, Forethought more considered, but also more transparent because they can then document that information. Cause they've really thought it through and present it up front to the candidate. I remember seeing, get your guide travel business based in Berlin and the way they did hiring was Like a breath of fresh air for me because as a candidate at the application stage, you would get information on the share appreciation rights, including actual values. You'd get links to your colleagues and here's the people on LinkedIn. You can look at their profiles. Here's what our team does. Here's how we're measured. Here's the products we work on. Here's like a day in the life. Like written detail of exactly what you'd be doing rather than just a list of tools and responsibilities and a generic sounding JD, I'm sure they could only arrive at that point once they'd actually thought of those things themselves, and then they could disseminate it to the candidates.

EMILY: Totally. I think there's a lot of, experimentation right in the recruiting process. And it obviously also depends on the scale of your company that you're hiring for. In a lot of cases, you start off with what you, typically have, a technical test, a case study or something along those lines. And I remember actually when I was interviewing for those sorts of positions, I actually appreciated doing a case study or proving myself, through the recruiting process, but looking back, it was long, right? And it did, it was very involved and it was one sided in a way. And I think the relationship between recruiting and, or employees have changed quite a lot, especially in tech. Where, yeah, it's more of a, dance and a tango where both parties really need to be on board with each other as opposed to, the power dynamics being solely on either the employer or the employee, which has happened, market in the past. But yeah, agreed. I think there's a lot of structure that you really do need to think about. And also for the team. In the company as well. If you're spending half your time interviewing people which has happened because we have a very small team, that's also not a great experience for anybody. So yeah, there's definitely a lot of intent. I think that people need to attach to the recruiting processes probably more so than ever before. But yeah, I think that like keeping in mind, the empathy or having empathy for both sides is I think a really good guiding principle.

TIM: Absolutely. What about hiring fails? Is there any particular moment or process that you remember that you're part of or that you saw yourself that springs to mind?

EMILY: yeah, I think the hiring mistakes come from a couple of things. So one is the technical skills. You index too far on them because you don't have a good idea necessarily what this person's supposed to out like the outcomes of what they're supposed to be doing. And it's easy for technical skills, right? The other side is that you hire someone with really great experience, but for a totally different type of company or a company of different maturity. So for example, especially from scale ups and startups, we have a tendency to look to Fang to source, new team members and to source new hires. Which they definitely have great experience and they have, a lot of value add potentially. However, you have to recognize that, Google, Facebook, Meta, et cetera, Netflix, they're all massive companies at this point, and they are operating on a totally different structure and they have a lot more rigor in some cases, not in others. And that can, sometimes not translate, into the structure and the culture that you're trying to build. So a lot of the early mishires or missteps I made in hiring are mainly due to those two things. And it comes honestly from myself, right? As a leader, I should have had a better idea of exactly what the profile I'm looking for, not just Oh, they have a great CV and I know that they can do good work, but can they do good work here? That's a very big difference between those two things

TIM: Yeah, I I feel like that kind of problem could be solved with the. Almost like ruthlessly honest interviews on both sides. where the candidate is like really. really telling you exactly what they need and what and how they operate. You're like, this is what we need and how we operate. Like how dating could be improved. Maybe this is some analogy there.

EMILY: No, for sure. I think there's a I use this analogy right where it's like hiring messy to be a goalie You know, he's a fantastic football player and a goalie is a fantastic football player, that doesn't work And so they realize he's a football player and let's just hire him for that goal You're like no that's a totally different thing. And so Yeah, that's not you know, that doesn't work so well, but I agree. I think I think recruiting especially You know, now that I'm on the leadership side, I recognize, and this is also part of diversity and inclusion, for example, right? You bring your authentic self to the workplace. I think it's super important because we spend, honestly, a lot of time at work and the people, that you spend time with in terms of colleagues and that you work with are oftentimes more than you see one's own family and friends. And so it's super important, I think, to be very honest with each other in the recruiting process to really suss out these, exactly as these, like these traits and these behaviors that either align or don't. And it's not, I think, something that I learned, now that I'm especially on the other side, but also later in my I see career right when I wasn't a leader or manager was that I realized that Especially in your middle to late part of the career, but can also work at the beginning you Really go through hiring or interviews Yeah, exactly. It's a two way street. It's dating. Exactly. As you said. And the more honest you can be with yourself and with the person that you're with the employer it makes it easier to understand whether you're going to be set up for success or not.

TIM: Silence.

EMILY: like, I've failed. I didn't get the job, but it's not a rejection. It's simply just that's just not the greatest fit for you. And there's something going to be, there's surely companies out there that are. More your vibe and that's totally fine. And yeah, I know vibes based like hiring is, a controversial subject, cause there's obviously a lot of bias in there, but I think bias is necessary in this particular case.

TIM: yeah, if I think back to the first few roles I had in my career, which were in some ways disastrous, to be honest the environments I ended up in and yeah, the fit or lack of fit for me personally I probably or definitely didn't have enough knowledge. Or wherewithal to know what questions to ask in the first place to even detect. Oh, hang on. If I rock up to the interview and the interview is half an hour late and it seems like you might be drunk, maybe that's like the red flag of red flags and I shouldn't be joining. and I feel like also maybe when you're more junior, you're the balance of power is so flipped the other way. You're a junior candidate. You've got no experience. You need a job. The company has a thousand applicants. You're one in a, one in a pile of people they could choose. But then I guess once you get senior enough your leverage increases a lot.

EMILY: I think there's also the case, right? I think where exactly as a junior person, it is extremely hard. And of course, where we're talking about jobs and livelihoods and, income, for example, things that you absolutely need for your life in general, the stakes are higher. So definitely understand, when the feelings aren't great when there's a mismatch, but ultimately, exactly. I think that You have this, you intuitively know when a place is right for you or not. And as much as we want to be data driven and we want to have You know, set people up for success, like that makes a big difference, I think. Yeah, I liken it to like, when I was a kid, I was always a theatre kid. But one time my mom sent me to sports camp, and I was just a fish out of water. I was just like, I don't know what I'm doing here. I don't know anything about what these people are talking about. My people, and I think that's the experience. I always hearken back to whenever I'm faced with this idea of rejection. I'm like, Oh, they rejected me. I'm like, no, it just wasn't good. It's going to be fine. You're going to find your tribe. It's going to be fine. And also I think there's also to be said about, companies are also evolving, right? Especially starters and scale ups. So even if they're saying no, or it's not a good fit today, Maybe three years from now or what have you, when they're at a different place, when you're at a different place, you can come back together. And it's not a personal judgment. It's just simply about, Oh, okay. You know what? This is not the right time, right place. Exactly. Like it's there's a lot of, that was actually

TIM: Yeah. I'm thinking about that now The candidate gets 1 percent of the feedback normally in this process. Like they'll get the no with maybe a one liner or a quick phone call in some markets, not even that. Yet there's probably been a conversation that's gone on a lot of back and forth, a lot of subjective comparison of candidates, ultimately choosing one over the other. And, I feel like the candidate misses all that nuance, which then makes the blow almost harder because it's no, it's like direct and rough. But if they knew how close it was and the reasons, as you say, which are just a timing thing, another person is better as different experience or whatever. I feel like that would lessen the impact of it and maybe help candidates not internalize each rejection. Cause it's like a lot of the times it's, Yeah, if you keep getting rejected for the same reason, like for 10 companies that told you the same thing, fair enough, but there's so much randomness in hiring, you can take it personally, like in sales, you get a lot of rejections, that's just part of it.

EMILY: totally. Yeah, I think it is hard, to, the, I don't want to invalidate everyone's emotional. And in fact, actually, I think it's important to validate the emotional aspect of recruiting. On both sides. I think one thing that is somewhat frustrating is as a employer, there are certain things by law that you're not allowed to say or speak to, or, something that might allude to company, inner workings that might not be like available to be public, but I do think Recruiting it's hard because there's so much volume of people, but I think it could do better by giving this feedback loop and having a more open sort of forum for those sorts of things to happen. One thing that is really difficult is, with all these moves of return to office and you hear these, I saw an article the other day about how. There's a lot of companies that put fake job descriptions on line just to make it seem like they're hiring, even though they're not. And those things are pretty insidious, which are just okay, but they're basically ways of manipulating the market in some way. But it's, yeah, I don't think that is the best way to go about it because ideally we have this situation where you interview somebody, Fair enough. You don't get through the interview stage. That's a whole other thing. But once you do get to the interview stage, there should be an opportunity for the candidate to at least understand, okay, this, these people are looking for this and I don't want to even give that potentially, which is totally legitimate. And, but yeah, we don't really have that. And I can imagine that those who are going through multiple interviews, multiple cycles, multiple types of employers. They never get this feedback and yeah, super, where do you go from there? That is very Yeah, it's also not great for society, I guess in the larger scope of things, right? Yeah, just more transparency and communication would always be well received. Let's say

TIM: I think so. And I feel like distrust, in most institutions is at an all time high. And now the narrative in the hiring market is was already, the ATS is filtering out your job, half of the job ads are fake, most of the job market is a shadow market, some of that stuff is bullshit, some of it's slightly true, and now there's the AI getting involved, so the companies are all complaining about, oh, half these CVs are fake, the candidates are saying there's 5, 000 of them, Candidates I'm competing with and it's just like an increasing level of distrust, which I feel like could be partly solved with a bit of transparency. And I hope that actually these conversations that we release would then help candidates because they'll see the people who are making the decisions that aren't evil and have a set of rationale and reasons they're going through and trade offs and subjectivity and a lot of grayness that I think a little bit of empathy on that side would then also reduce the paranoia, if I can put it that way.

EMILY: 100%. Yeah. I also see some generational shifts, right? I'm personally a millennial, obviously like an elder millennial, but in any case I've seen, the younger people on my team and the younger managers, especially have a very different view about how to run a company or what even a company means. So I think we'll see probably shifts in the next, I would say, 10 to 15 years as Gen Z and Gen Alpha, start to enter workplace and get into these leadership positions because we just care a lot less about the old guard of institutional structure. We've seen how, it just doesn't make sense as an employer when you're going through talent when you're going through recruiting. Exactly. It should be a personal, it is a personal matter, right? Like you are going to be working with these people and these people are going to be, again, like I said, like part of your day to day. And to imagine and to think about, I remember so at the beginning of my career, I remember applying for these massive multi corporate multinationals like uni labor or P and G and they had, psych tests and they had these like random things that you didn't even. Speak to a single person for about, five parts of the application and I think that's changing. I think of course that scale is very difficult, but just because it's difficult doesn't mean you shouldn't be able to do it right. And just because yeah, like it doesn't really lead to, I would say the ultimate success of people in the workforce as well. And yeah, I think there's just the power dynamic shifting to become a little bit more democratized. Which I think is a good thing for sure.

TIM: Yeah, absolutely. Changing gears a little bit. So cultural fit interviews and essential part of the hiring process or a red hot mess of bias. What do you think?

EMILY: I would say it actually depends on the size of the company. I think it's absolutely necessary if you're a small company to have a cultural fit interview. These people are basically in the trenches with you. And you really have to, I liken it to, you have a lot of analogies by the way, but one of them is you need to be being part of a small company, especially start-up and scale-up where everything is moving super fast, super chaotic. It's basically like you're all on this desert island and you're trying to figure out how to get off of it. And so cultural fit, I think, is extremely important for that situation because you have to trust that person, right? It leads to trust. It goes back to what you were saying about trust and being able to say I've trust that person to help me build the boat or to cut off, the fruits from the trees so we can survive. Over the next couple of years and I'm working side to side, shoulder to shoulder with them. So cultural input becomes extremely important. I think in that case, bias almost is an advantage just because you have the instinct of being able to say, okay, yeah, I don't have to worry about anything that's going on with this person's area because I need to focus on this other stuff, again, to get us off the island. I can trust, based on my subjectivity that person is going to do what they're not going to need to do. I think it gets a little bit more difficult at higher at bigger companies where I think you do have to have a lot more structure in place to avoid serious bias. And I think that's also where diversity ends up being more advantageous because you do need, I would say more of a consensual like perspective from, yeah, from multiple perspectives to achieve greater, greater impact and greater good. Whereas yeah, a small company, you're just putting a fire. So you're like, okay, can this person put that fire? Do I trust them to put out the fire next to me? Cool. Great. We can move on. But bigger company, yeah, that's more of a sense of, okay, let's make sure we're filling up, the gaps that we might be having, but might be might be missing. And and so I think that's where bias is. And this needs to be checked at the absolute least. Even then though, I would say that there is still a necessity for a cultural fit interview because of what I just said about how someone might be accustomed to working in a certain culture. But once you put them in this new environment, they don't work in the same ways or they behave a totally different way. And so that's another reason why I think the cultural fit is actually a necessary part of the process. Although it should look different depending on, yeah, the kind of company that you're hiring for this kind of team that you're hiring for.

TIM: do you feel like the concept of cultural fit and diversity more oxymoronic, I always feel like they seem like they're on the opposite ends of the spell, but opposite goals and how can you possibly have both, but I wonder if there's an aspect of it.

EMILY: I think that's the important part I think is that you, the culture part, I think is extremely important. You have to have a very good, solid, concrete idea of what your culture is in order to do the cultural fit. Otherwise, indeed, it becomes a, old boys club, essentially. Because that's what we're talking about, basically, right? In the old school way of thinking, cultural fit was like, Hey, is he my bro? Yeah, great. Cool. We're good to go. But I think in the new way of thinking, and when we're talking about culture, I think this is also something that tech has done really well for better for worse, right? Is that they have understood, okay, we do have a culture. And this is what those values are that are part of this culture. I think as long as you're pinning to the values, you can still hire for diversity. Okay. As long as those values are present and that makes a big difference, right? It's okay we value ownership. For example, anybody can be an owner, but they're not demonstrating ownership. Then, of course that's, that, that becomes a different kind of discussion. But I think it gets away from the old way of thinking, or like we'll say traditional employers who say, we don't have a, like who say we're doing cultural fit, but I'm like, what is your culture? You are a bank and there's no real, like what are the, you come nine to five, or nine to nine, depending on what your role is,

TIM: Maximize shareholder value. That's the culture.

EMILY: Exactly. Yeah. Yeah. And so I think that is that is something that is super important in the cultural phase. So if you don't have a culture, nail that down first before you do a cultural thing. And I think that can be really helpful. And that of course, if you're putting in values, You enable and empower actually a diverse group of people to say I can demonstrate those values no matter who I am or where I come from or what my education was, for example. Whereas yeah, exactly the old school way of like idea of just hiring nepotism, essentially some version of nepotism is really not, reflective of that for sure.

TIM: Yeah, if I reflect on how we've hired in the last five years our first attempts at hiring would fit into the kind of hiring fails category, but I won't go into the details of course, or name anyone. But then once we'd done a round and it hadn't really worked that well, then it was at that point that we sat down and concretely thought about. What values we currently have and what ones we want to have almost like aspirational values. We got that down in a confluence document. We gave clear examples at that point of how an engineer, cause we were mainly hiring engineers, how they could demonstrate this value and like the opposite, like an anti. Example of not demonstrating that value. And once we had that, then that helped us really frame the questions we were going to ask and the types of people we're looking for and what we would monitor for, but yet before that, it was just a, it's just too much of a gut feel or something.

EMILY: Exactly. Yeah. And I think that is also why at the beginning you're going to have to be biased, right? Cause you, you haven't really nailed down like what you're actually doing in the first place. Once you start to iterate upon that and reflect upon it, it does get a little bit easier. So ownership is a big piece. So Moonpay we have ownership as one of our cultural values. And in the beginning, ownership means a lot of things. But exactly as you said, we started to attach examples to it. It's this is a demonstration of what we consider to be ownership. And that made it a lot easier for one. The team itself like that was already here, right? We're like, oh, cool, cool. Okay, I can follow that. That's great I can I get that's a model I can apply and then exactly when we went to hiring it was no longer about oh, I guess like they own something But now it's no, they've actually demonstrated in the past whether that's on a smaller scale or a larger scale You know depending on the time type of role that you're hiring for they've been able to demonstrate exactly what they mean by value and that value, their conceptualization of that value is in line with our conceptualization, because that's also very important, of course.

TIM: Yeah. Let me throw another slightly different angle at you. So I was struck by something recently because I've just been to seven different countries, seven vastly different places, Saudi Arabia, Thailand, Germany, England, could not be more different to each other. And what I realized when you go there is the, Most people would adapt pretty quickly to the social norms of that place. I turned up in Riyadh. My friend said, Hey, like, why are you wearing sports shorts? Put some bloody pants on. I put pants on and then I was more appropriately dressed for everyone else walking around in Riyadh. Got to Bangkok. Then you can wear little shorts. It's fine. It's just, at most. Yeah. And also in Thailand, you You go and buy something or you have an interaction with someone, you can't just walk away after it. So there's a little bow, a little, a little thank you moment. It is, it's a more. Reflective or spiritual place. You get that vibe almost immediately. And so I adapt, maybe I'm reasonably agreeable and I can do it, but I was trying to think about this in the hiring context, because then if we keep selecting people in interview process for certain values, the company has on the basis of how they seem to perform it, then do we not discount those who could adapt? Could 80 percent of people just like. Go from a corporate to a startup and go, okay, I get it. All this bureaucratic red tape bullshit is gone. I can now just do stuff rather than having to report 50 times what i'm doing yeah

EMILY: I don't know for sure. I think that's a great question. I've honestly never really thought about before. I do think that is possible. And I think that also leads back to, again, I think you're the makeup of your team and the sort of team that you want to be running. Because I do think that there's opportunity to. Enable someone to adapt, but do you think that there are some fundamental things you can, question or that they should indicate we'll say during the recruiting process that will lead you to believe that they are adaptable. Ideally, they exactly demonstrate Oh, I have adaptable. Like I was in this environment and I was able to do that. I was also in this kind of environment. That's totally different. I could do that. And that also, that definitely leads to. Yeah, I would say that's a very good indication of how successful they would be. But I do think that there are, the flip side of that is, and I don't want to go into a negative space, of course, but You know that there are a lot of people who are not able to do that. And I think that's also something that you need to think about as a company, as to whether you want to, if you're able to take that risk. And that's also, I think for bigger companies, it's easier because you can take that risk, right? If you bring someone on board and they don't maybe adapt as quickly as possible or as in the way that you need them to in, in, in a certain timeline, then. That's something they can absorb. Whereas I'm a startup. If someone's not in line within three months, it's hard. And the things they're teaching so quickly that it's not a great experience for both places. So I think it does depend on the company itself and the maturity of the workforce in general., but I can see a world in which that would be possible and therefore we can, start to look elsewhere in order to, yeah, pump up, the sort of profiles that we have around the company.

TIM: changing topics a little bit. So AI, Chachapiti, large language models, all anyone hears about any day, anywhere in the world obviously can have profound impacts on numerous different roles, especially knowledge workers in general. What would you imagine the average data analyst might be doing in five years time, or if that's too far forward, sorry to think maybe even a few years time. Okay.

EMILY: Yeah, I think I think it's beneficial actually. Overall, I think it's a little funny to talk about AI and and, ML in general AI, especially within the context of data, because it is data at the heart of it. So there's a piece of which, it's exciting for data practitioners because we're at the heart of. The, the baseline and foundations of AI in general. So there's that piece. So I do think that a lot of roles will start to go more towards some version of algorithmic programming. It doesn't necessarily have to be machine learning or AI specifically, but definitely shaping the the thinking about what data functions at as a company is going to be. I think leaning more in towards both the business side and the business value of insights. As well as the technological solutions moving faster towards algorithmic provisions. So right now, in order to build these models, in order to build these we all know how, difficult it is to build a ChachiBT, et cetera, or GenAI products in general. Right now, the time to development is pretty long. For various number of reasons. A lot of it is exactly manual coding. You have to create some innovations that haven't existed before. There's a lot of time that one needs to spend on also the strategy piece, of course, whether this is valuable or not, and then of course there's the analytics piece, right? Where exactly is this value added? Whether it's just to an organization or to society in general, whichever. That, that takes, yeah, like I said, a lot of time. So I think there's a couple of things that Gen AI is going to help with. It would just basically speed that up. I think what data especially we're very conscious of is that we're still there to QA, right? Coders, developers, et cetera. We can probably put something into, Copilot or something along those lines and say, Great, I need a script that does this and this language and it needs to, output this. And it will do it for us, but we still need to go back, also because we're very aware of hallucinations and so forth, especially right now the technology being where it is. And so it cannot go, into the wild without that piece of QA, which a person definitely still has to do. But, yeah, it takes a lot less time to QA than it does to actually write the script and to write the code in itself. So I think that's the immediate the immediate aspect. But, yeah, I think at the end of the day, Data is going to, I think, change into a more I think it's already starting, actually. It's like bridging between the business and technology. And it and that's also what makes being a data practitioner really hard, right? Because you're a PM. But you're also an analyst, but you're also a scientist, but you're also an engineer, but you're also, there's a million has someone has to put on as a data practitioner. But I think AI will make that easier. And of course, we're also innovating towards AI being better than it is today as well.

TIM: I can imagine AI taking care of some of the entry level bullshit, data wrangling, whatever, and maybe lowering the barrier to entry for someone who's in those almost like shadow analytics roles Oh, they're a financial accountant or they're a business analyst or something. And now maybe with the help of chat GPT, suddenly Oh, cool. I wrote a SQL query. I can now get access to the warehouse and start doing Yep. a bit more self service, deep dive analytics and those kinds of things. Can you imagine that happening?

EMILY: A hundred percent. Yes. And that also makes it easier for data teams, right? I think there's a debate ongoing always, I think, about data and its function within a large company, or all companies rather, and all data teams I think have, I've been a part of, and also have, led and seen, have go through the same evolution of you start with being reporting dashboard. monkeys for lack of a better word. It's fine because you're learning the ropes, you're learning the business and you understand, how everything works, but it's not great, there's no analyst or scientist I know that loves that part of the job. They do it because it's a means towards a bigger end, which is providing insights, providing clarity, providing like actual value impact add to whatever the goal is. And so I think that the AI also helps with self service analytics, right? Because as a data team, it's impossible, or I don't think it's quite right if you have one analyst for every stakeholder in the business. Stakeholders should also be a lot better with their own analytics because analytics is a skill that is not, it's not reserved for data analysts. It's something everybody should be using critical thinking, for example, right? I know we all go to college and university nowadays, mostly with this idea that, oh, we'll get a job, but actually what we're supposed to be taught is critical thinking. And so I think that has been lost. a little bit, but that's also what AI I think is going to be really helpful with is that it takes care of the technological piece that is a little bit harder, exactly as you said, for the barriers to entry and enables them to apply the data learnings regardless of, what their skill set is in a wider format. And then, yeah, that one alleviates data teams from having to do that themselves. Also because there's sometimes a lack of context that you simply cannot have from years of experience. And then also data practitioners will be left to, or not left to, but they'll be enabled, let's say, to build even bigger, more innovative, solutions that can cover, massive frameworks and so forth that have a lot more just, yeah, just a lot more weight behind their solutioning.

TIM: if you think back to all the candidates you've interviewed in the past, there's something that typically separates the success cases from the fails, like the common recurring patterns. That you've seen over the

EMILY: Yeah, I think one of the main parts, so presuming they've passed the technical test, I guess that's a pretty low bar there for passing the technical test. But when it comes to, especially the behavioral part or what we're talking about, cultural fit, et cetera, I think one of the main things I've seen people falter on, for lack of a better word, is, Is on demonstrating, say, problem first thinking, and this is especially not only in data, but engineering as well, right? Because we're doing some really cool stuff, but it's very difficult or it's very it takes a lot of experience actually to understand. I'm building this to solve a problem. I'm not just building this cause it's cool and shiny and interesting, which is a risk, which is cool. Don't get me wrong. Especially when you're at a company, when you spend, let's just say three sprints or three months working on this project, and then you're trying to fit a problem to it, it doesn't work. And I also have another pet peeve where I really do not like it when people just present to me a list of problems. With no solutions. And so I think that those two need to come together. And in the interview process, we do try and make sure we enable candidates to answer and demonstrate, no matter how small it can be like, Oh, my manager said, I should do this, but I thought I was going to ask a few more questions and understand the problem first. And therefore I came to this other conclusion that worked well because of X, Y, Z. And yeah, I think that is mainly one of the things that people don't seem to understand, especially in technical roles, that the technological piece is really a means towards an end. Like I said, if not the thing in and of itself, I don't care if you built something really cool in a vacuum, but if no one's using it, if no one can use it, if it doesn't do anything, then there's no point really.

TIM: and would people in interviews almost give themselves away in the way they describe what they've done in their experience where it almost implies their mindset is, as you say, to do something cool, or it's just I built something as opposed to someone else who might present to the gods is really cool. We had a thousand signups in the first day and the feedback was X and they would present some data as opposed to the coolness, maybe. Yeah.

EMILY: That's exactly right. Yeah. So outcomes driven, mindset, I think is a really big thing, especially at a startup, right? But exactly a lot of the time especially even senior candidates, like people who are in academia, especially, I think they're unfortunately pretty guilty of this, but that makes sense. Cause in academia, that is the thing. You are doing the research, right? That is the outcome that you're going for, but unfortunately it doesn't really translate to the business. So yeah, a lot of the time the language is mostly about I built, I did. This is the methodology that I applied. I'm like, that's fine and nice, but yeah, exactly. If you can't tie it to the results. Or if there were no results, then that is a massive red flag.

TIM: what about if you think of your experience on the other side of the table as a candidate going for different roles, do any processes stick out in your mind as especially terrible or especially amazing? Thank you.

EMILY: Yeah, I think it goes back to what I was saying earlier about how when I was beginning my career, I was excited. I was hungry. I really loved, this idea of doing a case study and Doing this elaborate technical test. I remember for one of my interviews, I wrote basically like an essay, as to exactly what my thoughts were around the strategy and the data, et cetera. And at the time I thought that was great. I was like, this is a, this is also a really great way for me to learn. How to interview, which is actually a skill in and of itself, of course. But looking back, I'm like, that wasn't great. Because I think I spent, a solid, eight hours on some of these things, in which case, And that takes away, from other places. And at the time I thought this is a demonstration of my dedication. But now that I'm in a leadership role, I'm like, I don't want people to be breaking their backs over work. It shouldn't be the case. And so I think that at the time I assessed those processes to be pretty good and looking back, I'm like, they could have used some tweaking. And I do, yeah, I think that's, the kind of power of hindsight, obviously, but. That is, I would say, the extent of my terrible interview experience, which isn't that bad.

TIM: You've been blessed

EMILY: I have a bus. Yeah, I think I did have a an interview process that was really the most terrible experience was like not really an interview process. I'll put it that way but I was accidentally part of a production meeting at an ad agency that I once interviewed at I was there for three hours. I was stuck because I couldn't leave and I didn't want to make you know You I didn't want to make it awkward and be like, I'm so sorry and go to the bathroom, but never come back. That was awful. Cause that was also the very beginning of my career. I had no idea what I was doing. I had no idea how to work. And looking back, I was like, wow, that was extremely unprofessional. That had happened to me. I'd be mortified from the other side, Yeah, so that was not great. But yeah, I don't think it really speaks to processes themselves as much as it was just that one experience that I had, unfortunately.

TIM: there was another Emily L in the company or something like what happened? How did you get there?

EMILY: I think there was a double booking between me and the production company that was on this project, and it was a very small meeting. So it was a production company and then the agency and then it was me. And I think both parties thought I was just part of the other party. Yeah. And so I had to go back in and sign an NDA, about the contents of the meeting, of course and the funny thing is I didn't even, and I think they gave me they said they gave me a bit of an olive branch oh, come in for an interview next week, so I did do that, but it didn't go anywhere because they were like, I don't know, it was like, I guess it was visibly a mess, now that I look back, but it was hilarious at the time. And yeah, to this day, I'm still like, wow, what was that? That was very interesting.

TIM: A weird three hours in your life, that's for sure.

EMILY: Yeah, I think I even, because I thought at some point that it was a test as well. I was like, oh, is this just how they interview people? Okay, ​Wait, did I pass? Do I get the, do I get the Howard? And then later I was like, oh wait, this is not right. Three hours is a very long time for a test

TIM: That's, . what about this? One thing that's always struck me is, we've just talked endlessly already about AI. We're living this data driven world. Everything's becoming a bit more technologized, data driven. Including a business, including in product and marketing and sales and blah, blah, blah. Yet when it comes to hiring, traditionally, most companies still take a largely subjective, I would argue intuition based approach to hiring. And there's not that many things really that are measured closely. Why do you think that is? Do you have any views over that?

EMILY: so I think part of it is it leads back to I think what I was saying before about especially the type of company you are right smaller companies again, I don't think it's necessary to Like the rigor you're applying, the time it takes to have that rigor, just doesn't pay off, essentially. So I think that's, for the most part, why that is. But I actually disagree. I do think that the hiring process has become a lot more rigorous in the past, I would say, five to eight years. Five to 10 years. I would say with the rise of like big tech, especially, and just a lot more attention to exactly these recruiting processes as they happen. I think one thing that we are trying to do at Moonpay is calibrate exactly like some version of quantitative. It's not. We're recognizing that, when you're quantifying soft skills, especially or certain types of skills, it's not necessarily, it's a little bit arbitrary in some sense, but some quantification is even if it's just Oh, a one, two, or three. Is better than nothing. And we're also, I think, concrete tie, like making concrete, the soft skills. So it used to be like, Oh communication, like how do you measure that? But I think there are ways to measure that, right? It's okay, are you a stakeholder satisfaction, for example, some version of MPS, let's say internally, or even just observably, Hey, you just don't communicate that's poor. That is a zero on the scale of one to three, whereas three is like over Easy, audience considerations. tailoring your messages just in the narrative building overall. And so I do think that is changing. I think there is a lot more data driven. There is a lot more data behind recruiting nowadays than there ever was before, but I do agree. I think in some sense that historically it's been mostly subjective. I do think that, yeah, that goes back to, yeah, the culture of recruiting. Sort of discussion again, because it really depends on how you shape and desire those elements of your company. And so by nature, I think it has to be a little bit subjective. But yeah, I do think that it is changing in some sense. I do think that we need to be careful about not being too quantitative. as well. There's a world. And this is weird for me as a data practitioner to say, but I think instinct actually counts for a lot. It allows us, even when we're doing analysis or what have you, your instinct and your experience informed that first prior, basically let's call it like, let's a Bayesian prior for life, where you're just like, okay, I intuitively know that this is the way that we should go. Let's start there because there's a lot of data out there. And if you don't know where to start, even That's going to be an impossible task. And so intuition, I think, and subjectivity are really important to at least say okay, you know what, I think this is probably going to be the best way to start. And of course, along the way, there should be a little bit more rigor in, in between, but I don't think that there's a massive problem with, leaning a little bit more towards intuition and not being afraid of it. I think that's another thing too. You can still be data driven. And have intuition play a role, but being conscious of that balance, I think is very important.

TIM: Yes. What I would like to see in that scenario is a similar kind of thing to, so there's, yeah, the kind of cultural fit or any kind of subjective measure is if it's, if it just gets called out at the start of the process. So we might say, we're going to measure these technical skills and measure this and that. But then we've got this gut feel. Elements or like a likeability element of the candidate and just assign it a value and go this is worth 20 percent come up with any number you like, but we're still going to ultimately measure it. It's just incorporated to the overall measurement of the candidate. I think would be a good way to do that.

EMILY: Yeah, I think that makes sense. I think there's a, again, there's a risk, I think, to being too calculated with this approach, right? But I do think that there is something to be said about, it should carry some weight as to whether I actually want to work with this person. I think there's also something that we're getting away from in tech where it was, the asshole genius, which is very, was very persuasive for many years. It was like, Oh, that guy, he is amazing at what he does. He's a total dick. Nobody wants to work with him or hang out with him, but he's amazing. And I think we're all getting away from that because, yeah, day in, day out, no matter how brilliant someone is, at the end of the day, like you have to work as a team. And if someone's out there, doing their own thing, I guess that's about being a team player. Maybe there's a way to quantify that. But yeah, I think, that does count for a lot and more than I think that people, Want to again, it goes back to the bias part where, is this person actually an asshole or they just disagree with me? There's, but there has to be some reflection, I think as hiring managers as well on your own self. And making sure that you're aware of your own biases as you enter these processes for sure.