BREAST FEEDING IN NEW YORK WHILE CULTIVATING JOB LEADS FOR HER STUDENTS
Kreitzman made regular trips to New York, meeting with the managing directors and partners of the big banks and investment houses. She was making the cross country trip with one of her recently born sons when she still had to breast feed him. Long before there was Facebook, she created a Face Book of her students, becoming the first to give away for free a resume book of all her students to help them land lucrative jobs out of the gate.
“Since 2012, I was aware that data analytics and data science techniques were starting to be used in finance. I had people including traders telling me, ‘Do you have somebody who knows machine learning? So I turned to the operations research department and wanted to bring engineers to the program. We bring quants from the statistics department, math, computer science, and even MBAs. The beauty of this program is that we know our students before they start.”
‘NOTHING IS EASY IN THE PROGRAM’
The most difficult courses in program? Stochastic Calculus and Asset Backed Security Markets. “But nothing is easy in the program, Kreitzman says. What is very difficult for the students and requires killer time management skills is how to do everything at the same time. You have four academic terms of two months each. It is eight weeks of instruction and then a few days off and then you take your finals. After one week off, you come back for the second term, get another week off and in the third term you go to your internship. Then you come back and do it for two months and you are out and the next class comes three days later.”
What’s the difference between the more common master’s in finance and a master of financial engineering? The MFE, she says, has “very little corporate finance and project finance. Our courses are more quantitative in nature. In a more standard finance program, you can do a fixed income course and not require a project using Python (software coding skills).” There’s content on both machine learning and artificial intelligence. Finance is becoming more complex, with greater use of mathematical and statistical methods.
The Haas program is among a handful of the most prestigious in the world, along with those at Carnegie Mellon, Columbia University and Princeton University. Each year, Haas gets roughly 500 to 600 applicants for the 65 to 70 seats. “That number may appear to be small, but it is because we have an honest discussion with students. There is prescreening that holds down the applicant pool. I will ask people to bring a CV and transcript and we will tell you whether you are ready and can apply at an info session.” Roughly 60% of the students have only an undergraduate degree and 20% boast PhDs. She will admit little more than five or six students straight from undergrad. Most have had some work experience.
‘I HANDPICK THEM AND CAN TELL YOU THE GOOD, BAD & UGLY’
“No one is a slam dunk,” adds Kreitzman. “We interview every candidate, and I also conduct the final interview and that is the deciding factor. I know my students well. I hand pick them and can tell you the good, bad and ugly, but there is never any ugly because I pick them. In 2010,” she remembers, “I found someone who had everything. He was a dream student but lacked certain important skills. We realize the world is becoming more competitive. I need you to be good at math, statistics and economics. I don’t shape them to be good soldiers in the program. We work very hard to give them confidence without attitude. I work very hard so that they feel very comfortable when they are in the program. This is an elite program, but if you take time to prepare students they can be very successful. So preparation makes it accessible to more students.”
Tuition and fees for the program run $70,796, but the school estimates a student’s total budget, including healthcare, books, and estimated living expenses, should set you back about $106,000. Haas is increasing tuition and fees to $72,920 next year. While it’s not inexpensive, graduates do quite well, thank you. The majority of this year’s graduating class of 67 students easily found employment in the U.S. or London at such firms as Citadel, PIMCO, BlackRock, Squarepoint Capital, and Morgan Stanley. Their internships in big data, artificial intelligence, and machine learning at hedge funds, investment and commercial banks, and asset management firms set them up for lucrative job offers.
This year’s crop of students racked up a total of 122 job offers, with average first year total compensation of $160,083. The average first year base salary was just under $120,000, with average sign-on bonuses and relocation allowances of $21,730. The average first-year guaranteed comp came to $43,054. Add it all up and the first year comp package for one of her graduates this year came to a hefty $224,867. Most of the class went into asset management (39%) and investment banking (29%). Another 14% landed jobs in fintech and technology, 9% with hedge funds or trading houses, while consulting, rating agencies and investment research each took 3% of the students.
‘IF YOU DO WELL, YOU WILL MAKE A LOT OF MONEY’
“Everyone had an offer this year,” she notes. “Data science is hot, and the program changes lives.” One person in the latest graduating class had five job offers. “He had great firms, including Barclays, BlackRock, and Pimco. For three days he was very torn. He couldn’t eat or sleep. But I told him, ‘What a wonderful adventure. You are so sought after. You should be proud.’ He ended up at Balyasny Asset Management (BAM), a hedge fund. For international students today, it is also worrisome to look for a job. They don’t know what is going to happen with full-time jobs in this country. I am fully ready to place a student in London or anywhere else, if i have to.”
Even in the year after Wall Street collapsed, she placed 100% of her 64 students who received a total of 84 job offers, though first-year total comp in 2009 fell to $128,408 from $153,073.
But if you want to anger Kreitzman, just tell her you want to go into finance to become rich. “If you do well, you will make a lot of money,” she says. “When a student says to me they want to go into finance because they want to make a lot of money, it really rubs me the wrong way. I don’t like it because being an educator and having all this wealth of knowledge, I could have been a headhunter and made a couple of million dollars a year. But I am not crazy or foolish.”
“A lot of finance folks are dismissing this (as a fad). They think this is not here to stay. But Blockchain and cryptocurrency is here to stay. Data science is statistics. So in anything we do, the skill set to be able to do statistics is so important. We are making great strides. Some of my students are interested in self-driving cars and want to work for Uber as data scientists. Some are working on pricing strategies with companies and with real estate startups. It’s not just finance, and I actually say we hope to open the door to many places. They will be employed for the next 30 to 40 years.”