Are you looking for a highly respective quantitative program that will prepare you for a career in the most demanding, analytical, and data-driven areas of financial services? Today’s guest, Jacob Gallice, Executive Director of Berkeley Haas Master in Financial Engineering program, shares what it takes to get accepted to this highly competitive program.
Welcome to the 540th episode of Admissions Straight Talk. Thanks for joining me. Before we dive into today’s interview, I want to mention a resource at Accepted that can help you prepare your statement of purpose to a Master in Financial Engineering program as well as the other graduate programs. Download 5 Fatal Flaws to Avoid in Your Grad School Statement of Purpose to learn how to avoid the five most common mistakes we see in grad school statements of purpose, as well as tips on how to write a statement of purpose that makes your story memorable and highlights your qualifications for your target graduate program.
Our guest today is Jacob Gallice, Executive Director at UC Berkeley’s Haas School of Business’ Master of Financial Engineering. Jacob earned his bachelor’s at Binghamton University and his MBA at NYU Stern. He has worked for Goldman Sachs and Heidrick & Struggles in the financial services world. In 2017, he pivoted to admissions as Associate Director and then Senior Associate Director of Admissions at NYU Stern before deciding he preferred west coast weather and moving to Berkeley in 2021, first as Program Director of the MFE, then he became Executive Director of the MFE in March 2023.
So I can still, I think, congratulate you on your promotion, right? Still within 12 months. [1:56]
Congratulations, Jacob, and welcome to Admissions Straight Talk. [2:02]
Happy to be here.
Now let’s start with a really basic question. What is the Master in Financial Engineering program at Berkeley Haas, and what does it prepare one to do? [2:06]
Excellent question. A financial engineering degree is a specialized master’s degree here that prepares one to enter the field of quantitative finance and more largely, can prepare someone to enter the fields of financial technology, namely in roles such as data science, machine learning. But largely speaking, what we’re talking about here are individuals who are interested in the intersection of technology and finance and working within the ecosystem of what we kind of call the niche field of quant finance.
Can you provide an overview of both the full-time and the part-time options at the MFE program and roughly how many students participate in each of the programs? [2:48]
I can indeed. So we enroll about 80 students in our flagship full-time program. We’re one of the only programs out there in the market that is a one-year or 12-month program. So the program is intensive, it’s immersive, but it prepares students very well to enter and break into this field. So that is the one-year program. We can certainly get into that a little bit more in due course.
I contrast that with the part-time program, which gives students the flexibility to do their studies over a two- to three-year period, and it’s a much more small specialized cohort. Typically you’re looking at roughly 7 to 10 students in that cohort. It’s really designed for working professionals who are simply looking to augment their education, their studies, and apply that real world knowledge directly on the job. So we started that program a few years ago to sort of allow those students who otherwise did not feel it was necessary to leave their job, but still wanted to tap into the great education here at Berkeley Haas.
Do they basically have to be in the Bay Area for the part-time program? [3:59]
Actually they do not. No, we do allow students in that option to take their courses remotely if they so choose.
Is there an in-person component to the part-time program, and do both the online and offline students ever meet? [4:10]
The part-time is sort of what we kind of call a flexible first model. So students sort of have the option to do things in person. Of course they can come in person, they can be online, they can take components of it. So it’s sort of a choose your own adventure, if you will, on that side of things. And then of course, a lot of the information sessions, a lot of the lecture series, many things have continued to shift towards a digital first world as we figure our way out of this post-Covid era as you were. So a lot of our full-time students are also participating in things virtually. For that reason, the full-time and the part-time students do interact, whether it’s in person, whether it’s through their projects, whether it’s in classrooms. There’s a variety of different ways for them to interact.
I interviewed your predecessor in 2018. At the time she indicated that the MFE was going to focus more on data science. Today data science is much more prominent on the MFE website than it was five years ago. What’s the difference between a Master’s in Business Analytics or Data Science and the Master’s in Financial Engineering? [4:59]
Great questions. Business analytics is typically not even nearly as technical a degree as, let’s say, a financial engineering or a data science degree. So a business analytics degree would be the closer cousin of an MBA, let’s say, but gives students the opportunity to understand large data sets, obviously have an understanding of how to work in those roles, but they will not necessarily require the same sort of technical rigor that a financial engineering or a data science degree would.
Now data science, of course, is a large component of the financial engineering industry and ecosystem and having an understanding of data science and how to utilize big data sets is increasingly important for an aspiring quant finance professional, which is why we have continued to make that a part of our curriculum. And of course recently we’ve hired a fantastic new professor, a gentleman by the name of Professor Ali Kakhbod, who has taken over our deep learning courses, our data science courses here. So that’s been a great addition.
And then finally a data science program would be more industry agnostic. So someone who is pursuing that type of a degree might be interested in utilizing data science for healthcare or energy or another industry. So they might not necessarily have aspirations to work in finance per se.
So this is still very finance-oriented, obviously the financial engineering. [6:52]
What distinguishes Haas’ MFE from other MFEs or more commonly, an MS in finance? [6:56]
Yeah, absolutely. I’ll answer the first part of the question first. I already alluded to one thing earlier, which is one of the only programs out there on the market, which is to say we are a 12-month program as opposed to the traditional 18 months. Now, of course, that has huge implications with respect to a student’s return on investment, less time out of the workforce, quicker time to get back into the workforce.
Lower opportunity cost. [7:28]
Lower opportunity cost, right. So it’s all about that ROI. What we also do here is we’re one of the only programs that’s at a business school. Of course, that means that you have the opportunity to network with MBA students. You have the opportunity to tap into a business school’s resources as opposed to being, let’s say, hidden within a math department or an engineering department. So you have that amazing networking opportunity to be amongst the business school.
Then I’ll mention also location. So right now, there is such innovation going on within this industry. If you look at what’s happening with respect to new advances in the fields of artificial intelligence, all of that is happening right here in Silicon Valley, right here in the San Francisco Bay area. So the proximity to learn from people and to tap into all of that great innovation right here at your fingertips.
Now your second question was, how does it compare to a finance program? And that comes back to what we were just discussing earlier about business analytics, which an MS in Finance is a very different degree. It is not necessarily going to need the statistics, the mathematics or the computer science skills that a financial engineering degree would, right? Someone who’s going into an MS in Finance degree might be going into more of a traditional investment banking role, i.e. mergers and acquisitions, capital markets, corporate finance.
Wealth management. [8:48]
Wealth management. Right, exactly. So that will not prepare one for the rigorous field of quantitative finance.
What kind of academic background are you looking for in applicants to MFE, either the part-time or the full-time programs? I assume it’s going to be quantitative, but I’ll let you answer the question. [8:57]
It certainly will be quant, right? We can’t say that enough. I would say that you’re looking at some core themes. Math and stats, right? Rigorous math and stats training. Economics and finance. What do you know about financial markets and economics? Computer science, namely computer languages such as Python, C++. I would say these are the technical areas. Any coursework in machine learning is going to be helpful. What we typically look for though is those applicants who can combine that technical aptitude with strong strategic thinking and great intuition. How do you actually apply those things to a business setting? So it’s those applicants that we want to see apply to our program. Those applicants that we see could be really difference makers within their organizations after they do this degree.
Is there a leadership component also to the degree or not really? [10:07]
We have added some-
Strategic thinking or something like that? [10:13]
Yeah. No, it’s a great question. So this comes back to maybe the business school comment, which is you have an opportunity to participate in a variety of different workshops. We have also developed new workshops here in the areas, namely of negotiation, communication skills, and public speaking. So that is where we have tried to supplement some of the great technical skills that our students have.
My husband is a retired actuary, and he got to a fairly high level in his field. His biggest complaint or the thing that he felt was most missing, and again it’s a very technical field, was the ability to see the big picture. [10:36]
It is a very common theme. Yes, absolutely. Those who tend to be very technical sometimes have struggles to get out of the weeds.
What kind of experience do you like to see in your students? I’m talking about work experience now specifically. Are you looking for early career applicants, mid-career applicants, older applicants, especially in the part-time program? [11:01]
Yeah, absolutely. So I would say on average we’re looking at about two years of prior work experience. Again, there is a range. We do have applicants directly from undergrad. We have applicants with about five years of experience. Certainly on the part-time program, it does skew a little bit more experienced. Again, just because that is more for individuals who are just looking to stay within their current career paths as it were.
As far as what we look for, well, the best kind of work experience is at least related to what it is that you want to do. So any work experience that’s related to quantitative finance will be favorably looked upon, whether that’s research, whether that’s trading, whether that’s working as a software developer, these are all the things that would be helpful. Of course, working at a large financial institution would also be helpful as well.
Do you ever get career changes? Let’s say somebody who was working as a consultant and now says, “I really want to dive deep. I like the quantitative stuff.” [11:57]
Certainly we have seen… I would say that they have to be extremely committed given the niche nature of this field and given how technical you need to be, but supposing someone was working as a consultant, as a data scientist, then certainly that could be sort of a step in the direction here to make that kind of a change.
Can you describe the application process for the MFE? [12:27]
Yeah, absolutely. Very straightforward. We are going to be taking a look at a variety of different criteria. So we take a look at your standardized test scores. We’re going to take a look at your prior academics. How did you do in undergraduate? How did you do in any prior grad school? I will note that many of our applicants do already have existing graduate degrees. Again, not a requirement though. We’re going to be taking a look at your essays. We’re going to be taking a look at your prior work experience, which we just spoke about. Any internship experience. We’ll be taking a look at your letters of recommendation.
And then effectively what happens is we take a look at that completed application, and then there’s a round two, again, very different part of our process compared to some of our peer schools. Round two would be an alumni interview. We think it’s a very important part of our process. You would be asked to answer questions in all of the relevant areas, namely math, statistics, computer science, finance, to sort of simulate what it would be like to be in a job interview. We do that to make sure that you can be successful in this highly competitive field.
And in terms of the academics, can you just go into that a little bit more? [13:34]
Absolutely. So we’re looking for… Typically we like to see someone who has studied some kind of STEM background at the undergraduate level, math, stats, computer science, mechanical engineering. These are the kinds of things that we would look for. If you studied finance and economics, it’s not to say that we would not look at you, but how have you developed your math, stats, and computer science skills outside of your prior studies then, right? Have you taken CFA Level I? Have you learned it on the job? Have you taken online courses? Right? Because again, you will need those to be successful in this program. So that’s what we’re looking for in the academics. Have you taken the critical mass of coursework and studied discipline that’s relevant for this field?
And I assume done well in the courses? [14:22]
Doing well in the courses is also looked favorably upon for sure.
I noticed in preparing for the call, and you mentioned just a second ago that a lot of your students have graduate degrees, and I saw that it was roughly one third of the class has either a master’s or a PhD. While, it’s understood that graduate study is not required. Do you like it? I mean, is it something that helps? I would assume it helps people demonstrate the quantitative skills that you’re looking for, the computer skills that you’re looking for? [14:29]
We certainly do like it, right? We do think that it’s looked favorably upon, right? Because again, it shows that you have continued to demonstrate academic proficiency or gone deeper in a certain area. So if you already have a graduate degree in statistics, certainly that will serve you well for a program like this. So again, not a requirement, but certainly something that our admissions committee does take a look at.
It can also help with a little undergraduate grade repair, I assume. I’m going to guess that sometimes plays a role.
Are you planning to change the essay questions or have you changed essay questions this year and when will the applicants get them? [15:17]
Sure. So once you start an application, you will see the process. So you’ll get a sense of the essay questions. Largely, they are going to be pretty straightforward. They’re going to be around why are you deciding to apply for the program and what sort of path within this field would you like to pursue? We like to get a sense as to your understanding to making sure that you understand the field, to making sure that you understand that your goals are in line with your experience.This is sort of the question there that we’re looking at. There’s an opportunity for students to talk about any sort of issues that they faced prior with respect to their academics in case there was maybe a story or something like that that they’d like to share with the admissions committee. We’re going to have a question here about what do you think your strengths and weaknesses are? That is pretty straightforward.
Then we do have a video essay question as well. And this comes back to what we were talking about earlier, which is the most common thing that we see is extremely strong technical proficiency. But where we see our students sometimes lacking is, again, in those communication skills. The video essay is – little secret here: It’s less about what you say, and it’s more about how you say it. We want to see how you’re communicating. We want to see the little things. How are you speaking? What’s the tone of your voice? How are you enunciating your speech? Again, these are all critical factors to being successful in today’s highly competitive labor market.
The real question here really is to get a sense for your baseline communication skills. What we will sometimes see is that it’s very clear that someone is reading a piece of paper. So if they’re reading a piece of paper, that’s an indication to us that, hey, you’re not necessarily going to have the ability to think on your feet. You’re not going to necessarily have the ability to impress a portfolio manager if they are asking you a question you don’t know the answer to. We want you to take that question very seriously.
More about poise and presence? [17:30]
Are you concerned at all about the impact of ChatGPT on the essays and the application process? [17:34]
Concerned, I don’t know if it is the operative word there. I think this is the new reality in which we are all sort of living in. It’s obviously quite easy to use a tool like that to have it write your essays, as it were. It’s pretty obvious to someone when they’re reading that to see if it was done by a computer, or if it was done by a human. So again, don’t try to outsmart the admissions committee here. They’re going to know very quickly that it was written by ChatGPT.
But what I’ll say more broadly is these are new tools that people have at their disposal. So you need to be able to… The bar is now higher. You now need to be able to ask the right questions, put in the right prompts, recognizing that the answers are going to be very easy to get to. Right? Again, I’m not talking about our essay questions right now. I’m just talking about more sort of high level. The bar has been lifted, and it’s now going to be about asking the right questions. Again, that comes back to strategic thinking,
In terms of asking the right questions, you also have to check that ChatGPT is giving you the right answers. [18:44]
It doesn’t always do that. The other risk is that if you try and get it to think for you, you might get something that’s very generic. [18:52]
And plus, you have the video essay to confirm somebody’s communication skills, and if the video essay and the writing sample are completely disconnected, it’s not going to be good. [19:03]
It would not. No.
What can an interviewee expect if lucky enough to be invited to interview? [19:17]
Treat that interview the same way you would a professional job interview. Right? It will be conducted with one of our alumni. They will ask a series of questions, technical questions in some of the relevant areas, which I won’t repeat. They will ask questions about your resume. They will be given your resume. You need to be able to talk about those projects. You need to be able to talk about past internships. Treat it as you would a job interview. And again, they will also be getting a sense for your communication skills vis-a-vis that interview.
Do they have access to the other parts of the application or just the resume? [19:50]
Typically we would just have access to the CV.
Now, you mentioned the kind of jobs that MFE graduates are getting, but how does Berkeley Haas help them find those jobs? I assume some of the jobs are back east. They’re not all going to be on the west coast. [19:56]
Yeah. Actually a higher percentage of students end up back in the east than they do here in San Francisco, just given the number of finance jobs out in the east in New York, Boston, in those areas. So a lot of our students are out there in the market now. Because we run a one year program, we are running an idiosyncratic internship program. What does that mean? That means we don’t plug into the traditional summer internship. That means the program office here, myself and my staff, are sourcing bespoke opportunities for our students. That means they are not competing on the open market for a lot of those internships. It’s a huge differentiator, huge benefit to those students who like that model where rather than applying to, let’s say JP Morgan’s summer internship where you’ll be competing against every other student out there, thousands and thousands of applicants, we’re running an off-cycle internship.
So you’re basically given that opportunity to interview for bespoke opportunities on this off-cycle internship. These are posted directly on our job board, only available to our students, so it’s much less demand for those jobs. Then students are doing those internships. A certain number of students are converting those internships into full-time jobs while others will continue to recruit on the open market, as it were, for a variety of other different opportunities.
That is interesting. So is it January to March or something like that? January, February? [21:34]
Great question. This is what I spend most of my time doing is explaining this to employers. We run an internship cycle from October to January every year.
All right. [21:44]
October to January every year. Yep.
I can see that really being an advantage. Yeah. A tremendous advantage.
Now this interview is scheduled to air on September 26th. Your final deadline is October 5th, but the site says that applications will be accepted October 20th at I think 2:59 Eastern time or midnight, 11:59 Pacific time.
All this leads me to have two questions. One, do you really accept people this late in the application cycle? Because usually seats are given out earlier. That’s number one. And number two, most listeners to this show will be applying for the cohort starting classes in spring 2025. In other words, applying the following year. And what advice do you have for them? So it’s two different classes really that we’re talking about in these questions. [21:46]
Okay. Do we accept people after October 5th? Yes, we do.
How about just prior to October 5th also? [22:40]
And just prior to October 5th as well, right. So yes. I think that we are a rolling basis, but again, quality over speed, right? If there is a quality applicant that decides to apply late, we will absolutely have a spot for them in this program. We want to get the very best and brightest students. We do accept late applicants to this program.
Second question is what advice do I have? Prepare, prepare, prepare. Do not be the individual who is fortunate enough to get into this program or another amazing opportunity to study at grad school and then three months in or even a month in, frankly, start figuring things out. You need to do that preparation early. I’m not just talking about the technical preparation. I’m talking about trying to figure out what direction you want to go in.
We all recognize that grad school in and of itself is a time to do that kind of exploration. But again, because of the rapid nature of this program, you have to have at least a good sense of what you want to do to optimize your time here. Too often I would see a student come to me, let’s say a month before the internship starts and say, “Well, I all of a sudden want to do this, or I think I want to do that,” and by that time it’s too late. So prepare, prepare, prepare, and you would need to make sure you’re prepared in the technical areas. Make sure you have an understanding of the different areas within this field. That would be my biggest advice to you.
That’s great advice. I think one of the biggest differences between graduate school in general and undergraduate is when you start your college years, your undergraduate education, nobody expects you to know what you want to do. [24:09]
You just go to college. I think when you go to graduate school, you have to have a goal. Otherwise you might be spending a lot of time and money on an education that you don’t want or won’t use. So I think the” prepare, prepare, prepare” is outstanding advice. [24:21]
Listen, I’ll be the first to say, right? Some of the most interesting 50-year-olds I know don’t know what they want to do with their lives. But again, you need to be able to at least have a good understanding and sort of what we say, “Fake it until you make it.” So I think do that preparation. Life can always change. You can always make pivots, but you want to have the confidence in yourself to know the direction that you’d like to take.
And in terms of other preparation, I guess it would be making sure that you have the academic background that you’re looking for, right? [24:54]
What question would you have liked me to ask? What question would you like to answer that I haven’t asked? [25:02]
Well, I would say that one of the things that maybe we could get into here is just maybe a little bit more specifics of: I’ve just said to prepare. Well, that begs the next question, which is how?
So I think that what we do, and I’m happy to share some links here with this audience afterwards.
That’d be great. [25:26]
We have https://haas.berkeley.edu/current-mfe-students/requirements-conditions/ You need more work in math. We have some courses we recommend you take. You need more work in computer science. We have a list of courses that you can take to further prepare, right? Another thing that you can do, take the CFA Level 1, right? Great exam to get you prepared in some of the core foundational areas of finance. Other things, participate in competitions. You just can’t get yourself an internship. You’re not making it. There’s so many free ways now that are open to anyone and anyone. The opportunity is out there. You just need to go out and grab it. So I think just in terms of, okay, yes, you need to prepare. How? That’s how. Right? Go and do that.
I love that link. [26:09]
If you send the link, I’ll post it in the show notes for sure. [26:12]
I can do that.
That was a great answer. I’m so glad you asked that question.
Jacob, I want to thank you very much for joining me today. I’ve really enjoyed learning more about Berkeley Haas’ MFE program. Where can the listeners learn more about the MFE program? [26:15]
Yeah. Absolutely. And I will again share these, but I’ll just read the link out here. If you would like to learn more about our program, go to our website. All of those links will be shared with you in the show notes. Our website is a wealth of knowledge. I have yet to see a question that cannot be answered on our website, so please go ahead and take a look at that website. We’ve got student testimonials, alumni testimonials, our student blog, employment reports, including a full list of employers that have hired our students for both internships and full-time jobs. So just a great resource there for people who are interested in this program.
I agree. It is a great resource. So thank you again, Jacob. [27:06]
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