Searching Smarter Podcast: What Employers Really Look for in Finance Candidates

NOTE: While this transcript has been reviewed and lightly edited for clarity, it may contain errors. Please review the episode audio before quoting from this transcript.

Jesse Skaff:

Every year, thousands of highly technical, highly qualified early career professionals aspire to enter finance and the highly technical roles within. But only the best land the most exclusive opportunities. How do they stand out and how can more early career candidates stand out to achieve those aspirations? My conversation with Anthony Cheung from AmplifyME answers just that.

Anthony has spent the last 11 years of his career partnering with early careers candidates and institutions to create simulations and opportunities for the best new talent in the market, giving them a chance to hone their skills and stand out. Anthony and I cover a number of topics that offer loads of tips for a large cohort of future leaders. Anthony, great to have you here. Thank you for being on today.

Anthony Cheung:

Yeah, pleasure Jesse. Great to be here.

Jesse Skaff:

You've spent most of your career involved largely with entry level and early career talent. Talk to me about in this day and age where the bar for talent is.

Anthony Cheung:

I think that the perceived bar for talent is that it's gone up exponentially, which I don't think is necessarily wrong, but it starts to build in the perception that it's impossible to break in, which I also think is not correct either. So I think there's kind of two parts to that. The first part is I think that grades are no longer a key differentiator. And I think a lot of that's also come through a multi-decade change in how education has changed where it's become commercialized in a business.

I remember when I was at school, the pursuit was, you know, very few people got good grades. Whereas I think as the models evolved and business schools have become a business rather than academic institutions, I think the incentives have changed, which has meant then that the incentive is, well, these students have got to get good grades because they got to get the good jobs. And I think then by definition, more people have got good grades and it's become hard to see the signal from the noise. I don't think it's impossible, though, to break in.

And I also think that a lot of similar traits that have existed always have come back to the forefront. It's just about how do you identify the signal from the noise, as I said.

Jesse Skaff:

Do we think that the programs, the academic backgrounds, the tools at which all of these early careers candidates have at their disposal, has made people better than a generation ago, four years ago, nine years ago?

Anthony Cheung:

I think the tools have definitely supercharged the students overall in different ways. I think it's supercharged the access to information. So a good student should be using AI tools in the productive way of it's a coach and it's a means to, I'm sure when even when you're at university and like myself, Investopedia was like the Bible of all knowledge of how to be proactive and learn. Whereas probably nowadays you can just talk to Gemini or Claude and you get the sweet spot.

So yeah, I think that the access to those tools has changed. But then also the polished nature of the output then of the students means that they all look the same. It's almost impossible to identify. I mean, I talked to the hiring managers at these large institutions, 90% of the same.

What the student needs to plug that gap is they've got all the tools, but how do they get the experience? And that's something where I think that the university is that, you know, that's why we as a business exist. And we work with these business schools because we're the connection to them sitting on a desk doing the actual tangible role. The tools have risen the game, but it hasn't really solved that gap, which is everyone's got intellectually, technically better and can accelerate that process.

But that doesn't necessarily mean that they're going to be good at the job because they yet have yet to apply in practice those principles. They've learned about it. They've done everything looks great on paper. But until they put it into practice and we measure their performance in an assessed environment, do we then get to see how much of that translates into an end outcome of performance?

Jesse Skaff:

How does AmplifyME help candidates? How do they discern themselves? How do they separate from the pack? How are they able to allow themselves to kind of stand out?

And how can candidates themselves stand out?

Anthony Cheung:

One of the things that we're able to provide is I've always been frustrated by students. Throughout my 10 years of working with Amplify, it's always been the same. The kind of naivety of it is through different reasons that students tend to gravitate to quite a narrow selection of roles in finance. It's either I want to be a trader or I want to be an investment banker.

And we know that investment banking can be chopped and diced into multiple different disciplines within, you know, ECM, DCM and so on, so forth. But the students just see M&A advisory and trading and that's kind of the beginning and the end. So I think our simulations allow these students to explore is the main thing. Like the job I had in my first 10 years of career, I mean, I was training to be a professional athlete at the time.

I was a point guard National League basketball player in England. And I had no idea that the job that I ended up doing was basically I was a quarterback on a trading floor calling live market action to the traders. Basically, I was doing my job on the court that translated perfectly. I just didn't know and I didn't have a particularly strong economics background because it wasn't really an era of study that I had.

But I had all the fundamental disciplines of like the building blocks to be good at that job. So our Sims allow these students to do those classical roles, but explore more widely and for them to be able to then see the output of the metrics of what am I good at? Like I didn't know specifically my strengths and weaknesses. You get told at school these offhand kind of abstract comments.

But we live in a technological world these days where we can map quite comprehensively your behavior into specific data points and metrics. And it's like use that as a tool to understand yourself. Students I meet who are quite complexed about and feel pressures of what where do I go? What do I do?

It's kind of like, well, you need tangible evidence to support your decision making process. You need to be informed. So that's where our Sims really come in. And for an employer, then, if the student is better motivated, having found an area and discipline that they enjoy and are motivated in, I think you've just unlocked something really special, which is someone who's motivated when inherently do better because they not only have a skill alignment, but they want to improve.

They want to demonstrate this kind of growth mindset that we all desire as employers that are our next generation have. So that's what they get out of it. They get more highly motivated stuff. We've seen this at a big U.S. bulge bracket bank.

We've worked with them for a long time. The retention rate is much higher. So even in these high finance roles, because they've gone through this process of exploration and self opted in rather than followed the herd on campus, they stick around. So your return on investment is also improved.

And so it's kind of a win-win in that way in terms of how the students stand out. I think there's a couple of different ways I'd love to break this kind of archaic cycle of I went to school this school. I deserved this job or I got a first class degree or 4.0 GPA and like, give me the job sort of attitude. As we said at the top of the show, everyone's got one of those now, unfortunately.

I mean, I was just the benefit of being an old man now that, you know, my day we had a little bit more wider berth to maneuver in. But now everyone's kind of got those those grades as table stakes. So I always think to students, like, go beyond that and think about how can I provide the most powerful evidence to this employer of my desire to want to work for the firm or my fit for this role? So some examples of this would be joining a student finance society club would be one that's accessible to most.

Now, one student said to me, I can't get in like that. They're quite lock and key. And and then he just went about creating his own hedge fund society. He went on his own period of building some relationships.

He would send systematic emails at 100 email clip a time to hedge funds until one or two bit an email and came back and then had talks, started his own society. There's blogging. There's writing. I know a group of students in London have had a phenomenal uptake in their ability to network.

They created their own podcast and novel idea. These young people are so much better than me at the marketing aspect because they are native social media users. And so they can grow. I've seen this small group of students grow this podcast.

And it's crazy because they just they promote it so well on TikTok, on social, on Insta, in their forums, on WhatsApp, on Reddit. And that's being the key to them to just get extra access to build up their résumé, to improve their knowledge, to improve how they articulate market conditions, all the factors that help move the dial for you. So, again, I always go back to think of I say to students, think of a court of law, it's like a Netflix drama. You're there as the representee, the lawyer.

Right. You're Tom Cruise. And you've got this this student. Show me the evidence.

Whoever has the strongest and highest quality of evidence wins. There's no like, you know, I'm a nice guy. I'm a good guy. Great.

Show me. Demonstrate it rather than have this kind of perceived. I deserve it because I've done this. Got a good grade, gone to a good school.

It's got to be more than that.

Jesse Skaff:

What I also find interesting to what you just said is you didn't say anything specific about being the best coder, the best programmer, the math Olympiad champion. And by the way, we're not discounting any of those. We have clients that want those people, right? They want the math Olympiad.

They want the best programming triathlete that exists out of XYZ program. Absolutely. We're not discouraging those types of participation. I think they fall into the broader category that you just mentioned.

But kind of to your earlier point, it's not all just about can you do one thing the best with the tools. It's about how do you market yourself as a candidate. In a way, it's like, how do you fit yourself into the mold of today's society? But then once you're understanding that everyone's in the same kind of has the same starting point, then how do you stand out from there?

And I think it's not just there's not one key to unlock that lock, as you say.

Anthony Cheung:

Yeah, I mean, I think when everyone gets leveled up technically, we almost come full circle over the long term, which is back to human oriented behavioral traits as a marker of success.

Jesse Skaff:

That's exactly what I was thinking as you were saying.

Anthony Cheung:

Yeah. So if you distill down all the complexities out of it, the thing I hear more and more as a common thing out of the employers I talk to, is curiosity, effort, and resilience. If you possess those, you can become brilliant. And I think the understanding for young people is that, you know, you think about when you started at high school, you start at the bottom and you rise up the ranks, you become the top dog.

You go into the workplace, you go to the bottom again, got to work your way back up. But I think somewhere it's got lost. And there are reasons I think why it's got lost is that students think, no, because of this kind of lots of things, society, social media, compressing timelines of success and XYZ. You just think, well, I need that now.

But for everyone, there's a process to it. And it's funny you said about the quants because I totally agree there is a catchment of very highly technically proficient people that are needed. But interesting observations I've seen with some hedge funds is the quality of people's ability to code. That's something I'm really interested in to see how that evolves over the next 12, 24 months.

Because inherently, these are the earliest adopters of using these exact tools. And while these tools are very useful in that environment, when it comes to deploying live systems in the marketplace, like, of course, there's a human piloting this, and of course, you need to have the actual fundamental skills. So it'll be interesting to see whether that talent gets lazy over time because of the tools they have at their disposal. And then the other part on the quant side, which I also get from some of the firms we work with, is the art of communication.

Even if you're a highly technical, quantitative, oriented person, you don't sit there just coding all day in isolation. You need to talk to your PM. You need to work as part of a team laterally. You need to project manage and communicate your update and your status of where you're at with things.

Communication is key. So that's also become, I think, a bit of a lost art because the reward system praises technical achievement above all else. Whereas I think you need a bit more roundedness to it.

Jesse Skaff:

You've addressed my question exactly. And, you know, I think I've said this a couple of times on this podcast previously as well. I don't remember when he said it, but it was certainly this year. You know, the trait that Jamie Dimon actually still values the most and maybe even more than ever is critical thinking.

Right. You've mentioned curiosity. You've mentioned application of human skills and critical thinking. Even if you are using tech and tools, you still have to think for yourself, how is this going to apply to my scenario?

How am I going to present this information that I've derived? And that's just we can't overstate enough. Right. We can't overstate how much that kind of thing is important.

So, yeah, I think that's I think it's so interesting. I'm curious what the clients, you know, the institutions that you partner with and work with, because obviously, as you say, you know, you work with both hedge funds and banks. What they say to you, what they're looking for as well, if they find themselves to be caught in the only looking for the technical side, if they're starting to kind of, you know, come more around to the we want those human skills as well. Or if you're more consulting them on it to be mindful of being more open minded, what's the approach from the client side?

Anthony Cheung:

Yeah, it's very consultative, the work that we do with clients in a sense of different divisions within the company will have different requirements or key characteristics that they would deem to be desirable. Now, the best way of doing that in a more quantitative manner is to look at people who have had success that you would like to replicate. So actually, what we end up doing is our vision with what we do is to follow someone from what we call kind of grassroots from the first year on campus at university all the way through into their first 10 years of working. So they've gone beyond early careers at that point, and then reverse engineering and mapping the characteristics of the successful people.

And then looking within these data points that we capture along these different places on that roadmap to then look at the very beginning and say, well, who's showing some of those initial signals or signs? Now, what's really interesting about large institutions, as you will know, is that actually a lot of the stakeholders at these firms work independently of one another. The people who run the campus, the people who run the experienced hiring, the people who run this geographic region, there's different budget holders, they're quite siloed. There's no one common thread, whereas I understand these organizations are huge and they have big infrastructure.

But if you were going to start again, surely science would say that surely we should be mapping these individuals from point A to point Z and seeing how they progress through the journey to identify the potential leaders for our firm. And so that's really where we would fit is to try and try and do that. So we work with them in very bespoke ways to identify, well, what are those those hero figures look like? Let us run them through some of these simulation assessments to see what their underlying characteristics come out to the forefront and then look how we can start to then bring that into the development of some of the role specific simulations at the beginning.

So we could see what the correlations are.

Jesse Skaff:

I want to pivot a little bit to candidates, those early careers candidates in the modern meaning like now, end of 2025, 26, how they're applying AI, not just in the ways that we've already discussed. You know, we've kind of been building up the tech and tools conversation, what clients are looking for, you know, the institutions, how they should be evaluating said talent. A topic that comes up is interview processes.

If you're using AI in the job that you're applying for, should you be allowed to use it in the interview that you are applying for? And, you know, I know you have a couple of different stances on this, like maybe to an extent or whatever. And I want to hear that from you.

Anthony Cheung:

I think there's some different use cases that need to be identified first. So the traditional model is for a student to do a CV screening, cover letter screening, online assessments, so numerical, situational judgment, all that kind of stuff. Now, I have a close ear to our student community and AI tools are used 100% across that process. I have it on good authority from a major private equity firm that of their cohorts, they've seen online assessment tests go from around, I don't know, two thirds pass rate to 100%, first time ever.

No one fails because everyone cheats. It's like, welcome to 2026. So I think in those instances, those parts of the process for the applicant and the employer are broken. Student doesn't want to do it.

It has no value to the employer. So that's, again, where we would slot in and we have these assessments that are very much more simulating a situation to then look at behavior, which is very key to that. However, as you rightly said, AI inevitably is used in the workplace. You know, you would be remiss as an organization not to be adopting these tools for efficiency, gains, costs and so forth.

So what I would say is then, because we don't have a one size fits all simulation, it's very role specific. So we can get down in and work with these corporates about, well, you tell me your workflow and you tell me what tools you're using and to what extent it's being used. So for example, most big large institutions won't be using off the shelf. They'll have their own bespoke models that they're building internally.

So in that sense, we need to know not everything, but a little bit of that. And then we can incorporate that into the assessment. I think they should be allowed in these instances. But what's important is to what degree and how is the user using the internal AI system?

So the way that we would build it is if they switch over to Claude or Gemini, I can't track what they're doing. So we would have a native built AI solution within the platform mimicking the role, which then allows us to track as to what degree are they seeking help is the code where they can't solve a problem, simply a request to copy and paste. Or how has that process worked? And so I think there's ways and means of managing that to accommodate that this is a necessary skill set for most roles, but as to what extent and its use case, though, needs to be defined, essentially.

Jesse Skaff:

And, you know, I think what is not lost in that is where the evaluation can be is what we talked about in the point prior, right? How are you presenting the case that you're making? How are you communicating it, right? Are you waffling because you're trying to wait for the bot to give you your answer?

Are you direct as if you're speaking to a PM who has about 18 seconds to hear what you have to say and you get to your point and you say, this is what I'm trying to say. And this is what I need you to understand. And here's why I think you should invest in the stock or whatever the right, like the soft skills complement even the AI usage in interviews as well.

Anthony Cheung:

I mean, in interviews is a good point. I do think that this is why I've always had a bit of a bugbear about interviews because I think the way interviews fall short as a filter is that you can learn how to be really good at interviewing. Just practice, right? Feedback, iteration, practice.

And you could be terrible at a job and land it because you can interview really well. Now, what's been the key difference in the past, I think, is the ability to have access to interviews because historically, the interviews have been held to those who went to the best schools because they would qualify to get to the interview stage. Now, one thing that I think is really powerful now that levels the playing field, and I think that's a positive thing for talent identification, is that students should definitely use the tools for interview training. Like, I always say to them, like, I don't know, like, in my day, I would have had to have had a contact which coming from a lower socioeconomic background was a non-starter because no one was a professional.

Or two, you got to pay for it, which again, you know, mom and dad don't have the funds to pay for that. So I'm at a loose end there. So whereas now, use it intelligently. Practice, get critique, feedback, get it to time you, get it to simulate all the questions.

Being good at interviews is just repetition. And then I hope just like you train in a sport, the match comes and you are absolutely ready to perform. And you don't need the tools because you're confident because you've put the reps in, you know, the problem is, is that if you don't do the reps, in the end, as everyone knows, you're cheating yourself because then you get in the workplace and someone says, here's the 100-kilogram weight. You lift it for me and you go, I've not done the reps.

No way I can do that. So you're wasting everyone's time in the end. But again, I get why students do it, but I encourage them if anyone's listening, use the tools, no one's saying not to, but use them in the right circumstance. A live interview is your chance to shine.

And when all employers tell me that it's refreshing when there's an authentic conversation. I mean, so you, so how do you differentiate? You differentiate by not using the tool in the live environment in a rather perverse way.

Jesse Skaff:

I think it's a great penultimate point for us to close with just general candidate sentiment, you know, who the cohorts that you're working with, what they're thinking about, we've talked about how they can stand out. We've talked about how they can apply themselves and present themselves. What are they thinking? The groups that you're working with, the early careers individuals, as they enter the workforce, as they are in the first couple of years of their careers in this mid and early stage AI world, what are they thinking about what's driving them and how are they trying to succeed and stand out on their own?

Anthony Cheung:

Yeah, yeah, yeah. I mean, I wrote down four points that I think when I thought about this in advance, that really summarizes it. And it's anxiety, it's competition fatigue, it's uncertainty around AI, because we see these headlines all the time. I read one this morning in the UK Times, a student had an offer, got rescinded last moment.

Why? Reading between the lines, AI has displaced an early careers role because of the nature of it, a consulting-type role. Sure. So there's fear of automation, essentially.

So with all of that, it's not an easy fix. Because when you think about a lot of those things, anxiety, for example, it's a psychological one that can't be remedied quickly. So I think my words of encouragement to any young person is to fundamentally try to focus on the process and not the outcome. You don't have control on the latter, but you can certainly have influence over the former.

Right. So everything we discussed about the accumulation of experience through your own perseverance of creating opportunity and demonstrating then validity of your argument. A lot of that is it within your control? I spend so many sessions walking through the step by step on how to do these things to students, but only around I'd say 5% actually go ahead and do it.

And the reason why is always, and it's a lot of work. And I say, well, welcome to the real world that you're about to embark on, which is the hard work is really what will pay off in the end. And, you know, again, I go back to sport because that's where my heart kind of is in my kind of life is the best players are not, you know, talent doesn't get you to the professional league. Talent is only one part of the equation, and it is hard work and turning up day in, day out, persevering, performing when you don't feel like performing.

That's what makes greatness. And that's what then ultimately yields results. So I think there's a bit of a reframing that needs to happen, that needs to think less about outcome and more about process. And ultimately, that's trying to adopt a growth mindset over time, which I know is easier said than done.

I can't if we had many hours and weeks of training, I could probably get people there. But yeah, that that's my kind of summary, I guess, to close.

Jesse Skaff:

You're a basketball guy. All I kept thinking, and I thought you were even going to say it there, all I kept thinking was mamba mentality. Kobe Bryant's whole journey is that it's about the journey, not the destination with connection.

Anthony Cheung:

And this isn't planned, but I was coached by Kobe's dad in an Adidas camp in the summer of 96. I think it was we used to have all the best players in the country come together for an Adidas camp. And I remember Kobe when he was like 18, 17, 17, he was not great because he got drafted the next year. Yeah, he was not great.

I mean, he had he had a lot of confidence, don't get me wrong, but he was not great at the start. And then here we sit, he's one of the most decorated champions of all time. He has this ideology that you said the mamba mentality, which exists, but he's a byproduct of the problem with social media and the accelerated timelines is I remember Kobe from 17. Whereas most people remember Kobe from the end product, the multi decorated champion, the Olympic winner, the MVP.

He wasn't that person at the beginning. And in fact, those first few seasons, but nobody is exactly. And so he has talent, but talent needs to meet determination and consistency. And that's what, you know, in the end, will yield results.

Jesse Skaff:

Wonderful. That's a great place to end our conversation. And I think you've encapsulated so much valuable information for an enormous cohort of young professionals and aspiring professionals. So thank you for being here. Thank you for your insights. And I hope to have this conversation again.

Anthony Cheung:

No worries, thank you.

Jesse Skaff:

That's all for today's episode of Searching Smarter. If you found this conversation valuable, be sure to subscribe so you don't miss an episode. Until next time, keep searching smarter.