1. What is financial data science and risk management (FSRM)?
2. Can I enroll in the program as a part-time student?
3. What is the difference between the FSRM master's program and the MS in Statistics program at Rutgers?
4. What is the differences between the FSRM master's program, the MS in Mathematical Finance (MSMF) program, and the Master's in Quantitative Finance (MQF) program at Rutgers?
1. What type of background should students have?
2. What is the prerequisite coursework for the FSRM program?
3. What are the requred GRE and GMAT scores?
4. What is the application process? What are the deadlines?
5. Can I start the program in Spring?
6. If I enroll in the MS in Statistics program at Rutgers, can I transfer into FSRM later?
7. If I enroll in the MS in Statistics program at Rutgers, can I register for special FSRM course sections?
8. If I enroll in the FSRM program, can I transfer to the MSMF or MQF programs later?
9. I have attended or am currently attending a graduate school. Will my credits transfer?
10. Can you give some guidance about the required recommendation letters; can they be either professional or academic?
11. Is working experience necessary for entering the program?
12. I notice that my TOELF scores are below the requirement in Listening/Speaking/Reading/Writing part. Am I still eligible to apply?
13. I have attached my profile (including CV, GPA, GRE/TOELF scores). Could you please tell me whether I have any chance for admission?
1. What types of careers are available for graduates?
2. Does the program arrange for internships during study?
3. What kind of placement services does the FSRM program provide?
4. How successful has the program been at placing its students?
"Financial Data Science" as a discipline is the application of statistical methods to problems which arise in finance. It is NOT a reference to "financial data science" as used in common parlance where the phrase can refer to the actual price data about stocks and flows. In recent years, a great need for the development and implementation of fast and sophisticated statistical methods has arisen in the financial industry. Financial data science addresses this need. Methods from financial data science are essential for processing the massive amount of data available throughout the industry, extracting useful information from this data, exploring arbitrage opportunities resulting from market inefficiencies, automating the asset evaluation and selection process, optimizing portfolios, and evaluating risk exposure.
Risk Management is a field that is closely related to financial data science. Here the main objectives are the identification, evaluation, management and on-going monitoring of risk exposures. It includes credit risk, market risk, operations risk and enterprise risk management and involves learning the techniques for identifying, estimating and managing risk e.g. thru risk hedging, risk/return optimization, and regulatory compliance in finance – all essential issues in modern finance. Effective risk management requires a deep understanding of uncertainty and probability and a high level of skill in statistical modeling, data analysis, estimation and prediction. Knowledge of financial markets and instruments and the major regulations that apply to financial institutions like the Basel Accords and the Frand-Dodd legislation and related agency rule makings is also part of the training.
Yes. You may enroll in the FSRM program as a full-time or part-time student. Most FSRM courses will be taught during the evening at the Rutgers Busch campus (in Piscataway), in order to accommodate part time students who work during the day. We encourage applications from those who are currently working in the financial industry and wish to further advance their careers by upgrading their statistical modeling and data analysis skills.
What is the difference between the FSRM master's program and the MS in Statistics program at Rutgers?
The FSRM program is a professional master's degree program that is designed to train students for immediate post-graduation employment in the financial services industry or in financially focused departements of enterprises e.g. Treasury. The coursework and training that students receive in the FSRM program is focused on teaching statistical and related data analytical and computational tools required for quantitative analyst positions in the financial services industry, as well as related finance, finanical markets and regulatory content. Only financial data and applications are used for course projects. Such in-depth training is most suitable for students with a strong interest in working as quantitative analysts in the financial industry. On the other hand, the MS in Statistics program is less specialized, with coursework and training concentrating on general statistical methods. Graduates of the MS in Statistics program are prepared to continue their studies towards a Ph.D degree, or to seek employment in various industries, such the pharmaceutical industry, marketing, and consulting, as well as the financial industry. Though some of the course content required for the FSRM and MS in Statistics programs overlap, special course sections that emphasize financial applications are reserved for FSRM students. These special sections tend to be more demanding, with challenging problem sets that often involve the analysis of real financial datasets, and written projects and oral presentations, which help to hone students' skills for the financial workplace. In addition, in the FSRM program, regular faculty are supplemented by bringing in practitioners for certain courses or course sections.
The three programs are related in that they all aim to train students to work in the financial industry. While there is some overlap in course contend, each program has a different focus. This is reflected in substantial differences in the programs' requirements.
The MSMF program is a mathematics program. It focuses on mathematical models for financial asset pricing and the related numerical methods required to apply these models. Typical applications of these methods include complex derivative security pricing.
The MQF program trains students to become financial managers and professionals in corporations and enterprises, as well as financial institutions, with expertise in corporate finance, portfolio theory, and corporate structures and re-structuring.
On the other hand, the FSRM program is a statistics and data analytics based program, tailored to train the next generation of professional financial data scientists and risk managers. The graduates from the FSRM program will be able to take immediate employment as financial data scientists and risk managers dealing with issues of uncertainty and risk identification and mitigation rather than complex derivative pricing and complex derivative product development. The FSRM program is most suitable for students who are interested in statistical and data analysis for large financial data set, identifying statistical arbitrage opportunities, proprietary trading strategies, stress testing, simulation and risk management.
Admissions and Courses
Students should have completed an undergraduate degree with a major in statistics, mathematics, or a closely related discipline, such as physics, engineering, or computer science. Students from all over the world are encouraged to apply to the FSRM program. The majority of our applicants have not worked in finance and do not already have a graduate degree, though we will consider students who have related work experience (which can be very helpful in securing an internship) or those who already have a master's or PhD in other subjects.
Successful applicants must demonstrate a high aptitude for quantitative reasoning. They must have a firm grasp of mathematics and statistics at a high undergraduate level, which includes at least multivariate calculus, linear algebra, and statistical methods. Basic skills in computer science and computer programming are also a prerequisite. More detailed information is available at our prerequisites and requirements page.
The Graduate School generally expects successful applicants to have verbal and quantitative Graduate Record Exam scores of at least 500 and 600 respectively. Our requirement for the verbal score is somewhat flexible, but successful applicants are likely to have quantitative scores considerably higher than 600. For students submitting GMAT scores, the typical requirements are a verbal score of at least 29 and a quantitative score of at least 46. Again, the requirement for the verbal score is somewhat flexible.
Please note that, as part of the BS/MS program, GRE/GMAT score submissions are waived for Rutgers undergraduates with cumulative GPA of 3.2 or better.
Applications are made through the Graduate and Professional Schools Admission Office and not through the FSRM program directly. You will need to provide official transcripts, three letters of recommendation (professional or academic), a personal statement, GRE or GMAT test scores and TOEFL or IELTS test scores (international students). Please see our admissions page for further details on the application process, including deadlines.
Transferring is possible, but not guaranteed. A maximum of nine credit hours of course work (which typically amounts to three semester-long courses) can be transferred to the FSRM program provided they are approved and have not been used to satisfy the graduation requirements of another graduate degree. Students in the FSRM program are required to take more demanding, specialized sections of some of the courses required for the MS in Statistics program. Students who have completed non-FSRM sections of these courses and who are seeking to transfer credits to the FSRM program may be required to complete additional work, such as a written project, before receiving credit for the FSRM program.
The special FSRM sections often have a very limited class size to achieve the desired learning experience and are reserved for FSRM students and for other Rutgers Quantitative Finance programs which have reciprocity with FSRM (include Math Finance and the MQF program
It is possible but not guaranteed. Evaluation of transfer applications to these other programs will be based on your performance in the FSRM program and other considerations. If you successfully transfer from the FSRM program to another program, credits earned in the FSRM program may be transferrable as well.
Yes, you can. However, the program is designed for full-time students to graduate in three semesters. Full time students entering the program in Spring might need to stay for the fourth semester depending on students' background and course availability. Part time students usually do not have this problem due to their flexibility in course selection.
There is no “transfer” from one university to Rutgers. You must first apply and be admitted. Discussion will only occur after an offer of admission has been made. Permission to transfer will be granted on a case-by-case basis and will not be granted automatically. Students can apply to transfer up to 9 credits for graduate courses, provided they replace appropriate courses offered by our program, and credit for such courses was not used to earn a previous graduate degree.
The recommendation letters can be either professional or academic. It is completely your choice.
You are still welcomed to apply. Your application as a whole is more important than individual scores and weaknesses can be balanced by strengths in other parts of the application. However, if your scores are much below the requirement, we suggest that you should retake the test.
Unfortunately, we cannot give any opinions about admission until we see your full application, including transcripts, test scores, and letters of recommendation.
There is considerable demand for people with advanced statistical training, like that obtained in the FSRM master's program, throughout the financial industry. A few areas which rely heavily on employees with such training include trading, risk management, and portfolio management. Additionally, many of the largest and most widely known investment banks and hedge funds employ people with an advanced statistical skill set.
The program strongly encourages students to participate in summer internships with financial companies and will do its best to help students obtain internships through its connections with the financial industry.
We help graduates secure employment by utilizing our connections with recruiters and the financial services industry. Students have an opportunity to attend industry career days, financial company information sessions and campus visits as well as other networking events. Student resume books are distributed in print and online to potential employers, and a designated Student Gallery on the FSRM website exposes students to recruiters and financial institutions. Additionally, career development support is available through required workshops in resume writing, interviewing skills, professional networking and other job search tools. English as a Second Language (ESL) courses are required for non-native English speakers on basis of a language skills assessment. ESL training is provided on a non-tuition basis in the entry Fall semester.
ALthough our program is relatively new (our first class entered in fall 2011), most of our students have found employment either before graduation or within one to two months of graduation. We expect to continue to place our students well.