Introduction to MFE at Berkley Haas
Your career builds momentum from day one in the Berkeley MFE Program. In one intense year,* you gain the knowledge and skills to have immediate impact in a complex finance or data science role.
At Berkeley Haas, you master the theories and frameworks underlying today’s complex financial markets and gain insights into how they play out in the real world—through applied projects and an internship. Your professors are among the leading minds in finance. Your classmates come from around the world and from across disciplines, contributing diverse perspectives and expertise to discussions and team projects. No wonder the Berkeley MFE Program is consistently ranked a top program of its kind.
3.72
Avg. GPA
26
Avg. Age
2.6 Yrs.
Avg. Exp.
87
Class Size
24
Months Duration
Quick Overview and Rankings
7
QS Top MIF
Tuition Fees & Scholarship at Berkley HAAS
€ 80,486
Tuition Fee
+
€ 33,932
Living Cost
Avg. Cost of Study
The Tuition fees for Berkley HAAS MIF is $80,486 and an additional $33,932 in living cost.
A Berkeley MFE degree is an investment in yourself. Financing any major investment can be challenging, and Berkley is committed to help you explore all the financing options available, including scholarships and loans. Which can help you build a financial bridge between your MFE tuition costs and your career goals.
Important Scholarships
- Mark Rubinstein Fellowship
- The Chengchun "Arthur" Qi Book Scholarship
- The Ekaterina "Kate" Matrosova Leadership Award
Employment Prospects about Berkley Haas
Employed within 3 months of graduation
Avg. Salary
Most Sought-after Jobs
Financial Analyst
Investment Banker
Portfolio Manager
Risk Manager
Financial Consultant
Corporate Treasurer
Hedge Fund Manager
Private Equity Analyst
Top financial institutions and technology companies consistently hire Haas graduates as interns and full-time employees. Employers are drawn to Berkeley MFE students for their mastery of powerful quantitative and management tools, coupled with a robust understanding of best practices in the changing technological, global, and human dimensions of business.
The employment report from the program showcases the career trends, hiring patterns, and salaries of the most recent graduates.
- Goldman Sachs
- JP Morgan
- AQR
- BlackRock
- Citadel
Eligibility Criteria : MFE at Berkley Haas
Technical Knowledge and Experience
Applicants should possess experience with computer programming (C++, Python) and familiarity with computers as a computational and management tool; statistical and econometric applications (Example: R); and machine learning concepts.
Candidates should have excellent writing, speaking, and presentation skills (in English).
Work Experience
Post-university work experience is preferred but not required. The MFE also admits undergraduate students with strong academic background with little to no experience.
Documents Required
- Online application form: This includes your biographical information, educational background, work experience, essays, and letters of recommendation.
- Official transcripts: You must submit official transcripts from all colleges and universities you have attended.
- GMAT or GRE scores: The GMAT or GRE is required for all applicants. The Haas School does not have a minimum score requirement, but the average GMAT score for admitted students is 720.
- Résumé: Your resume should highlight your academic achievements, work experience, and any other relevant skills and experiences.
- Two letters of recommendation: One letter of recommendation should be from a professional supervisor who can speak to your quantitative skills and work ethic. The other letter can be from a professor or another academic who can speak to your academic abilities.
- Optional essay: The optional essay is an opportunity for you to tell the admissions committee more about yourself and your motivations for pursuing an MFE degree.
Application Deadlines : MiF at Berkley Haas
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Specializations and Electives Offered
The program kicks off with an informative and social orientation. During this week-long introduction to the program, you’ll get to know other new students and gain a sense of what the classroom experience will hold. The orientation features team-building exercises, lectures, and workshops on special topics, including a thorough overview of the job market and career resources.
For detailed term wise information, please visit here.
FAQs about Berkley HAAS
What is the difference between an MFE and other degrees?
MBA: The differences between an MFE and MBA are numerous. Some of the differences are obvious, for example the MFE program is one year, while an MBA typically takes two years. The MFE is a Master’s degree in a specialized type of Finance, and an MBA is a more general, well-rounded business degree. Courses you might expect to take in an MBA program would be in Marketing, HR/Management, Accounting, and Finance. In the MFE program, we only cover these topics as they relate to the specific field of financial engineering. Most MBA programs do not require the high level of math, analytic ability, or computer programming experience required by the MFE program. The combination of skills obtained by MFE graduates (understanding of complex financial strategies, financial modeling ability. and computational proficiency) are difficult for employers to find in graduates of standard MBA or Engineering programs.
PhD: A PhD can take 5 to 6 years and is recommended for students who want to pursue a career in academia. To some extent, the MFE may be seen as an attractive alternative to a doctoral program in finance for those interested in commercial rather than academic careers.
CFA (Chartered Financial Analyst): Many people in the finance industry get their CFA in addition to advanced degrees in finance. The main difference is that a CFA is an independent certification process, not an academic distinction. For some jobs it is desirable to have both, but they are not interchangeable by definition.
What type of students do Berkley HAAS look for?
The MFE program looks for candidates with a background in finance, economics, statistics, mathematics, engineering, computer science or other similar quantitative fields.
