I think a huge reason a lot of students who come from a quant background want to go into front office roles is because how the media portrays the life style, also due to the higher earnings potential that is associated with sales since your compensation is proportional to what you bring to the firm. But I think what alot of media and people leave out is the work life and stress associated with these positions. People who tend to do well gain energy from interacting with people like that all day. So trying to compete with someone who has a natural affinity for their roll most likely won’t work. It’s probably best not to force your self to do something you don’t enjoy just to chase a small pay increase and instead focus on what you enjoy since you’ll stand out alot more when you enjoy your work.
@@DimitriBiancothank you for the reply, this is true but I believe in their mind they are trying to get in the best financial situation possible. I think it’s a lot of social media culture and family pressure . I know many people training for interviews in fields they have no interest going into but I see the stress coming off of them. Because their families or UA-cam are constantly throwing out insane unrealistic numbers in their face so they feel pressured to earn at that level. I see it all the time as chatter, “I heard so and so made 350k coming out of undergrad”…., and since alot of these exaggerated numbers percolate up it sets unrealistic expectations that this is how much a 24-26 year old should be making. So i really appreciate the content you have made talking about realistic expectations for the felid not just throwing huge numbers on screen trying to catch an audiences attention by promising them numbers that maybe the top 1% of applicants see.
Great video! I couldn't agree more on preparing for interviews. I was confident with my CV and what I could do in the role. But the hiring manager caught me off-guard easily. I wish I prepared more so that I wouldn't miss such a great opportunity. Lesson learned, in a hard way ...
I just found your channel recently and I've been binging your videos like crazy. I'm set to graduate with a master's in statistics this fall, and the job application process has brought me a lot of stress. I failed to take a data structures and algos class in my undergrad, and I'm just starting out with Leetcode stuff, so I've been having a ton of difficulty passing technical assessments even though I KNOW I can do this if I just get 2-3 more months of grinding. Your content is great for me. Sometimes I can recognize that I'm not in the right headspace to be grinding practice problems or learn some new algo, but I also feel the need to do *something* that feels productive. Your vids are informative, fun, and I always come away from them feeling like I got a lot out of it even if I'm not in the right headspace to really capital L Learn something new. You might not see this, but seriously thank you so much for all that you do. If it's not too much to ask, I have a quick question (I'll respond to this comment)
So I've been applying to a ton of DS/Quant roles, but really what I want out of a job is intellectual. I don't really care much about the subject matter, the industry, the job title, or the pay (to an extent), but what I want to do is use statistical modeling and programming to solve problems. I would prefer work that uses SQL/Python/R/SAS/whatever but I would accept stuff in Excel as long as the people around me know a little about VBA, array formulas, and are generally power users. My question is: What's a really underrated job title/industry/area that a new grad might overlook which isn't as "sexy" as Quant/DS but is filled with smart people doing interesting modeling?
@@DimitriBianco In addition to the question I asked earlier, I have another little Q to ask if you don't mind: Do you know anything about electricity quants and quant trading in electricity markets? I understand that a lot of the work in those markets involves the US power grid and location-based pricing, which means a lot of graph theory/network analysis. Was wondering if you had any insights into what the job is like and how the interview process is. I have a technical coming up soon and I figured you might have some insight being from Texas. Love your vids man. Keep doing what you're doing!
What you said about layoffs was interesting to me. If companies lay people off, why do they still hire people? Why don't they just keep the people they have? Are they hiring people with less experience to offset the costs of keeping someone who's more experienced? I'm just trying to make sense of layoffs vs hiring.
Hi Dimitri, I had a quick question about difference in interviews on buy side vs sell side for quant research positions. Pretty much all buy side jobs state that they don’t require any finance background and only test you on probability, cs, and stats. Is the same true for interviews on sell side? I can’t find much info on this online.
It depends a lot on the firm for both the buy-side and the sell-side. There is a general attitude by quants that finance is easy to learn and math is hard to learn (there is an interview with me coming out soon on another channel about this www.youtube.com/@sourcecodepodcast3720 ). The reason for this attitude is that math builds so you can't skip topics very easily. With finance (and business) you can often just pick a topic and learn it without a lot of other base knowledge. Now when I hire (and most on the sell-side) we want some finance knowledge as it is just one less thing to teach. The finance piece could be the small difference when making a job offer however you MUST have a string quantitative background.
Thank you for the video and clear explanation. I'm a Senior Software Engineer with over 20 years experience. I have a BS in mathematics and love math and statistics. Ive been wanting to make a career change. Now that the SE job market is flooded, do you think now would be a good time to learn how to be a quant?
If you have the time it could be a good time to reposition career wise. To be honest though, the quant market feels crowded. There are constantly new masters programs popping up. I think there are more than triple the programs today as there were 9 years ago.
What is graphed on the y axis at 1:39 ? I’m looking at US gross federal debt and total government expenditures from FRED and it looks nothing like this
@@DimitriBiancothanks. The big step up is because they included the amount of money in savings accounts starting 2020. But your point still stands. I wonder why it has started to go down 🤔 maybe people buying bonds.
RE: amount of social interaction. I'm in an academic track but flirting with the idea of transitioning into QF. Correct me if I'm wrong, but I always imagined actual quant jobs (so not glorified data science or dev roles) to be somewhat similar to academic research in the day-to-day, meaning a not insignificant portion of your time is spent in small groups discussing and bouncing ideas off of each other's heads. Could you maybe clarify this?
It depends where you are but it is less academic than that. Typically you are given a problem to solve and have a timeframe that it has to be finished within. For example, I need a model to predict loan defaults and it is due within three months. In that example, we know the most common models used and will look to see if there are any special requirements which could change that. In that example I would start with WOE transformations and fit a logistic regression model. There is a lot of data cleaning and other tasks that fall into the project as well which is why 3 months really isn't that long. If I were to explore and try to create a completely new framework I often won't hit the deadline. Companies are there to make money and quants are there to solve their problems quickly.
In regards to the social interaction, everyone has to pull their weight as to contributing to the bottom line. This often results in a senior quant assigning work to a junior quant but there isn't a ton of meetings and fun exploration of ideas.
Hi Dmitri I am trying to get hourly data for around 50 stocks for 10 years.Can you point towards free and reliable sources. This is for a personal resume project.
i don't know anything about economics, so i was wondering if you could explain why the lower class can't feel the effects of the "extra/free money" but still feel inflation (i am in the lower class and i make the same minimum wage as i did pre-2020 but now have to pay more for groceries).
This is a great question. I left out a bunch of information to make the video shorter but here are some other factors. The groups I labeled as classes were actually credit score ranges (think FICO ranges) which typically align with class. The x-axis is extra money being applied to debt. If I remember correctly the max value of $1,000+ meaning people were spending an extra $1,000 per month on debt over a longer period (I believe the data is 2 years). So to get the right tail, someone would need to have over $1,000 in debt payments. The lower class would have a low probability of having that much of a debt payment as they don't make as much income. Someone making say $100,000 would be able to take that on however someone making minimum wage wouldn't have the funds (this depends what state you live in as minimum wages vary a lot). Since the groups were actually credit scores, this would make it very challenging for an individual with a low score to be accepted for that large of a loan. In the industry we typically consider DTI (debt to income) or PTI (payment to income) when making the decision to issue a loan. This limits the total consumer loan size. The other factor which was a part of the original presentation was student debt forbearance. I somewhat glossed over this in regards to the chart. The average student loan payment is between $200-$500. Less people in the lower credit score range go to college compared to the other groups. This means those who had student debt could stop making student loan payments which would artificially increase their income by $200-$500 depending on how much student debt they had. Then you stack on the government checks to get the increase in unearned income. To summarize all of that, there were obviously some in the low credit scores paying off debt however they have less debt in dollar terms and saw less of an increase in income due to student loan forbearance not impacting them. Many of them went to spend their government money on other things besides debt which is understandable however that isn't shown in the chart.
Textbook? Naw, we just go out and garden => oh shit, that's my solution. Solution? Yeah it comes out of your ass/air => look for evidence that it works.
I think a huge reason a lot of students who come from a quant background want to go into front office roles is because how the media portrays the life style, also due to the higher earnings potential that is associated with sales since your compensation is proportional to what you bring to the firm. But I think what alot of media and people leave out is the work life and stress associated with these positions. People who tend to do well gain energy from interacting with people like that all day. So trying to compete with someone who has a natural affinity for their roll most likely won’t work. It’s probably best not to force your self to do something you don’t enjoy just to chase a small pay increase and instead focus on what you enjoy since you’ll stand out alot more when you enjoy your work.
I agree. It's what makes it frustrating to teach quant finance on UA-cam lol. I get a lot of people who are chasing dollars for the sake of dollars.
@@DimitriBiancothank you for the reply, this is true but I believe in their mind they are trying to get in the best financial situation possible. I think it’s a lot of social media culture and family pressure . I know many people training for interviews in fields they have no interest going into but I see the stress coming off of them. Because their families or UA-cam are constantly throwing out insane unrealistic numbers in their face so they feel pressured to earn at that level. I see it all the time as chatter, “I heard so and so made 350k coming out of undergrad”…., and since alot of these exaggerated numbers percolate up it sets unrealistic expectations that this is how much a 24-26 year old should be making. So i really appreciate the content you have made talking about realistic expectations for the felid not just throwing huge numbers on screen trying to catch an audiences attention by promising them numbers that maybe the top 1% of applicants see.
Great video!
I couldn't agree more on preparing for interviews. I was confident with my CV and what I could do in the role. But the hiring manager caught me off-guard easily. I wish I prepared more so that I wouldn't miss such a great opportunity. Lesson learned, in a hard way ...
I just found your channel recently and I've been binging your videos like crazy. I'm set to graduate with a master's in statistics this fall, and the job application process has brought me a lot of stress. I failed to take a data structures and algos class in my undergrad, and I'm just starting out with Leetcode stuff, so I've been having a ton of difficulty passing technical assessments even though I KNOW I can do this if I just get 2-3 more months of grinding.
Your content is great for me. Sometimes I can recognize that I'm not in the right headspace to be grinding practice problems or learn some new algo, but I also feel the need to do *something* that feels productive. Your vids are informative, fun, and I always come away from them feeling like I got a lot out of it even if I'm not in the right headspace to really capital L Learn something new.
You might not see this, but seriously thank you so much for all that you do. If it's not too much to ask, I have a quick question (I'll respond to this comment)
Feel free to ask questions and thanks for being a part of the channel!
So I've been applying to a ton of DS/Quant roles, but really what I want out of a job is intellectual. I don't really care much about the subject matter, the industry, the job title, or the pay (to an extent), but what I want to do is use statistical modeling and programming to solve problems. I would prefer work that uses SQL/Python/R/SAS/whatever but I would accept stuff in Excel as long as the people around me know a little about VBA, array formulas, and are generally power users.
My question is: What's a really underrated job title/industry/area that a new grad might overlook which isn't as "sexy" as Quant/DS but is filled with smart people doing interesting modeling?
@@DimitriBianco Thanks for your response! Question posted below :P
@@DimitriBianco In addition to the question I asked earlier, I have another little Q to ask if you don't mind:
Do you know anything about electricity quants and quant trading in electricity markets? I understand that a lot of the work in those markets involves the US power grid and location-based pricing, which means a lot of graph theory/network analysis. Was wondering if you had any insights into what the job is like and how the interview process is. I have a technical coming up soon and I figured you might have some insight being from Texas.
Love your vids man. Keep doing what you're doing!
Thanks for the video! (Tech / QD / QSWE here going through the season as an international)
Good luck with the job search!
Looking for jobs in risk management for a quite long time, your video is really really helpful!!!
sell-side work is loads more interesting than the buy side anyway. the challenges that the problems pose are much more thought-provoking
So true, I’ve done both and I think sell side was the most exciting work I did
What you said about layoffs was interesting to me. If companies lay people off, why do they still hire people? Why don't they just keep the people they have? Are they hiring people with less experience to offset the costs of keeping someone who's more experienced? I'm just trying to make sense of layoffs vs hiring.
Video response coming in the next few weeks.
@@DimitriBianco Great, I'll look forward to it!
Hi Dimitri,
I had a quick question about difference in interviews on buy side vs sell side for quant research positions. Pretty much all buy side jobs state that they don’t require any finance background and only test you on probability, cs, and stats.
Is the same true for interviews on sell side? I can’t find much info on this online.
It depends a lot on the firm for both the buy-side and the sell-side. There is a general attitude by quants that finance is easy to learn and math is hard to learn (there is an interview with me coming out soon on another channel about this www.youtube.com/@sourcecodepodcast3720 ). The reason for this attitude is that math builds so you can't skip topics very easily. With finance (and business) you can often just pick a topic and learn it without a lot of other base knowledge. Now when I hire (and most on the sell-side) we want some finance knowledge as it is just one less thing to teach. The finance piece could be the small difference when making a job offer however you MUST have a string quantitative background.
@@DimitriBianco thanks for the reply!
@adityapillai7670 thanks for being a pat of the channel!
This video is so helpful!! thanks
Thank you for the video and clear explanation. I'm a Senior Software Engineer with over 20 years experience. I have a BS in mathematics and love math and statistics. Ive been wanting to make a career change. Now that the SE job market is flooded, do you think now would be a good time to learn how to be a quant?
If you have the time it could be a good time to reposition career wise. To be honest though, the quant market feels crowded. There are constantly new masters programs popping up. I think there are more than triple the programs today as there were 9 years ago.
What is graphed on the y axis at 1:39 ? I’m looking at US gross federal debt and total government expenditures from FRED and it looks nothing like this
That chart is the FRED M1 money supply.
@@DimitriBiancothanks. The big step up is because they included the amount of money in savings accounts starting 2020. But your point still stands.
I wonder why it has started to go down 🤔 maybe people buying bonds.
RE: amount of social interaction.
I'm in an academic track but flirting with the idea of transitioning into QF. Correct me if I'm wrong, but I always imagined actual quant jobs (so not glorified data science or dev roles) to be somewhat similar to academic research in the day-to-day, meaning a not insignificant portion of your time is spent in small groups discussing and bouncing ideas off of each other's heads. Could you maybe clarify this?
It depends where you are but it is less academic than that. Typically you are given a problem to solve and have a timeframe that it has to be finished within. For example, I need a model to predict loan defaults and it is due within three months.
In that example, we know the most common models used and will look to see if there are any special requirements which could change that. In that example I would start with WOE transformations and fit a logistic regression model. There is a lot of data cleaning and other tasks that fall into the project as well which is why 3 months really isn't that long. If I were to explore and try to create a completely new framework I often won't hit the deadline. Companies are there to make money and quants are there to solve their problems quickly.
In regards to the social interaction, everyone has to pull their weight as to contributing to the bottom line. This often results in a senior quant assigning work to a junior quant but there isn't a ton of meetings and fun exploration of ideas.
@@DimitriBianco Thank you for your answer, that is quite helpful actually! Would you maybe say then that the buy-side has a more academic atmosphere?
Hey Dimitri! What's your view on Certificate on Quantitative Finance (CQF)? How helpful do you think is it to break into the industry?
Hi Dmitri I am trying to get hourly data for around 50 stocks for 10 years.Can you point towards free and reliable sources. This is for a personal resume project.
If you are a student you should look at QuantConnect. They often give high quality data to students for free.
Dimitri, now that the market is in shambles, is it a good idea in your opinion to go for a phD and finish it by the time this recession slows down?
I recorded a video response. It should come out in the next few weeks.
@@DimitriBianco Thanks Dimitri for your time. Just a request: if you can make a video about the "mock interviews" I would really appreciate it.
i don't know anything about economics, so i was wondering if you could explain why the lower class can't feel the effects of the "extra/free money" but still feel inflation (i am in the lower class and i make the same minimum wage as i did pre-2020 but now have to pay more for groceries).
This is a great question. I left out a bunch of information to make the video shorter but here are some other factors.
The groups I labeled as classes were actually credit score ranges (think FICO ranges) which typically align with class. The x-axis is extra money being applied to debt. If I remember correctly the max value of $1,000+ meaning people were spending an extra $1,000 per month on debt over a longer period (I believe the data is 2 years). So to get the right tail, someone would need to have over $1,000 in debt payments. The lower class would have a low probability of having that much of a debt payment as they don't make as much income. Someone making say $100,000 would be able to take that on however someone making minimum wage wouldn't have the funds (this depends what state you live in as minimum wages vary a lot). Since the groups were actually credit scores, this would make it very challenging for an individual with a low score to be accepted for that large of a loan. In the industry we typically consider DTI (debt to income) or PTI (payment to income) when making the decision to issue a loan. This limits the total consumer loan size.
The other factor which was a part of the original presentation was student debt forbearance. I somewhat glossed over this in regards to the chart. The average student loan payment is between $200-$500. Less people in the lower credit score range go to college compared to the other groups. This means those who had student debt could stop making student loan payments which would artificially increase their income by $200-$500 depending on how much student debt they had. Then you stack on the government checks to get the increase in unearned income.
To summarize all of that, there were obviously some in the low credit scores paying off debt however they have less debt in dollar terms and saw less of an increase in income due to student loan forbearance not impacting them. Many of them went to spend their government money on other things besides debt which is understandable however that isn't shown in the chart.
@@DimitriBianco thank you for the great explanation, makes a lot more sense now!
Just open: Wolf of Wall Street.
Show: I'm a Quant.
Why? Lemme just short bro.
Textbook? Naw, we just go out and garden => oh shit, that's my solution.
Solution? Yeah it comes out of your ass/air => look for evidence that it works.