New Series- “Meet our Financial Math Alumni”- Coffee Chat with Jonathan Leonardelli

"Meet our Financial Math Alumni" is an up-close interview series with select Financial Math alumni to learn more about their career, experience and knowledge after receiving their Masters in Financial Math degree from NC State University. Alumni are important part of our program for many reasons. They provide support, vision and strategy to ensure the success of our program. They are role models and mentors for current students. They strengthen the reputation of the Financial Math program. They provide job leads and recruitment activity for students. Our alumni are intelligent and awesome! Thank you to those who participant in this series"- Leslie Bowman, Director of Career Services


Meet Jonathan Leonardelli, FRM, Risk Consultant (Graduated 2004)


Interview conducted and summarized by Yi Chao and Xiaohong Chen, Financial Math Interns, May 2015 Graduates

Jonathan is currently a Risk Consultant at Financial Risk Group. He is also one of the first students to graduate from NCSU’s Financial Mathematics program. We were honored to have the opportunity to interview him.

Part I: Education & Job Background

1) Interviewer: Why did you decide to get a Masters in Financial Math at NC State?

Jonathan: I had just moved here and was interested in changing careers. I wanted to find a program that combined mathematics and finance. As it happened, NC State was in the process of creating the Financial Mathematics program. Although the start of the program was still a couple years off, that time allowed me to get the necessary mathematics background I needed. Entering the program produced the exact result that I wanted: it gave the mathematics I need to do interesting work in the banking industry.

2) Interviewer: How did the program prepare you for your job?

Jonathan: The program really gave me the depth of math that I needed to work in the field of risk. It also taught me how to apply rigorous logic to a problem to help find a solution. Beyond this, though, I learned that life was filled with randomness. This randomness, as a result, causes the quantification of some metrics to be difficult.


Part II: Analytic techniques

3) Interviewer: "Big Data" is a hot specialization in the field. Do you see this as long term trend or something that might pass as a fad?

Jonathan: It is definitely not a fad. In this day and age many actions we take, especially when using a piece of technology, is probably captured and stored in some database. Now, think about all those action and all the data that comes along with it. What is a company going to do with this data? They are going to improve their sales, improve their risk practice…the list goes on. Having skills to work with big data, to be able to find the relevant information and then integrate it into a model, is very useful.

4) Interviewer: The trend of “Big Data” implies that historical data can shed some lights on future prediction. However, this contradicts with “efficient market theory” to some degree. What are your thoughts about this?

Jonathan: I think concerns should always be involved when using historical data because the tacit assumption is that the future is going to behave like the past. That being said, there are ways to mitigate these concerns. For example, when we calibrate models one of the first things we do is test it with a different period of data to see if the model is robust. Sometimes we might use the model on data representative of a stressed scenario (i.e., a scenario that is uncommon but still possible) and see how the model performs. If it performs badly, we try to assess why that is. Are the parameter estimates wrong? Are different variables needed?

5) Interviewer: Does your company use stochastic models to predict interest rate? What kind of models are used?

Jonathan: To be honest, in my current job the main stochastic (i.e., diffusion based) models I have used are CIR (Cox-Ingersoll-Ross) and GBM (Geometric Brownian Motion) with the occasional jump-diffusion model thrown into the mix. Most of the models I have worked with recently are linear regression, logistic regression, and Markov chains.

6) Interviewer: In your area of specialization, what is your favorite method or model and why? Do you believe it is perfect?

Jonathan: Markov chains and their resulting transition matrices. This comes from the years when I worked in the banking industry. At a glance, the transition matrix tells you the behavior of different segments of accounts. Depending on how the states of the Markov chain are defined, the transition matrix can tell you: 1) The probability of going to default, 2) the probability of paying off, 3) the probability of curing, 4) the probability of moving across multiple states over a given time, etc.

The transition matrix is a great summary tool. Of course, it is not perfect. Always keep that in mind when you build a model. Even though the model looks pretty and deals well with the data – now – it is not perfect. It is an easy move from complacency, when the model is performing well during good times, to anxiety when the model is performing poorly during a financial crisis.


Part III: Risk Management

7) Interviewer: How do the regulation policies enacted after crisis affect the behavior of your company?

Jonathan: The regulations have not impacted the behavior of our company. However as a risk consulting company, we have seen more requests from financial institutions asking us to help them comply with the regulations.

8) Interviewer: The goal of risk management is to achieve a balance between returns and risks. Thus, with a lot of capital and human resource spent, risk management may, to some extent, reduce a company’s profits. Driven by the motivation of maximizing the profits, will the companies pay enough attention for risk management?

Jonathan: I may be biased, given my chosen career path, but I think with the recent financial crisis still fresh in our memories as well as all the regulations that were created as a result of it, businesses will continue to pay enough attention to risk management. And, I think, it will be that way for a while.

Part IV: Suggestions & Advice

9) Interviewer: Any tips for those interested in getting into the field?

Jonathan: First, be comfortable with the idea of randomness. Randomness is uncertainty and uncertainty is risk. Second, companies do not only seek candidates that are good at math and programming. They also seek those candidates who can clearly present their ideas in writing and presentations. Third, get perspective from areas outside of mathematics. I strongly suggest taking business classes because it gives you a different view of a business. A company is multifaceted and does not solely revolve around models.

10) Interviewer: What courses do you recommend?

Jonathan: The courses in the Financial Math program are very good. Among them, I definitely think the probability course is the most important one. That course takes you deep into the world of randomness and, hopefully, makes you comfortable with it. If you have an option of taking a course on risk or financial regulation that would be good. I took econometrics as an elective and, more often than not, draw upon the math tools I learned from that class more than others. Another very good course I took, and have used frequently, is time series analysis.


"It is a great experience to interview Jonathan. He is humorous and smart. We learned a lot when we talked with him. Thanks Jonathan for participating in our interview! We are sure that your answers will shed some light for those interested in Financial Mathematics!"- Yi Chao and Xiaohong Chen


A student’s interview experience- the benefits of planning and preparing for the big day!

Internship Interview Experience at a Financial Security Company

(Disclosure- this is a true interview story. This student received an offer and is currently working at this company. Her interview experience and interview format is typical but may not reflect all interview experiences. For privacy reason, the interviewee and company are made anonymous.)

I had an interview with the risk management model group of a financial security company. The main financial products of the company are mortgage loans insurance and long term care insurance.

The interview lasted two rounds, and each round covered two parts with two interviewers from the risk management model group. In the first round interview, the interviewer mainly asked about some questions ranging from mortgage loans, basic statistical knowledge of data mining to regression techniques and models. (Tip- Researching the employer was an important part of this round.)

Questions about mortgages loans referred to concept of premium, prepayment and interest rate. The interviewer introduced their mortgage product to me and I expressed some of my points of view about the product combined with financial terms that I learned in some related classes. (Tip- show employers your educational knowledge through related courses.)

In the basic statistical question part, I was asked about questions of distribution of certain scatter plots that were prepared by the interviewer. Besides, the interviewer asked me to come up with some fast data mining methods that can help a modeler quickly deal with data in an efficient way. (Tip- be prepared to show examples of your quantitative skills)

Most technical questions were focus on regression. The interviewer discussed with me two econometrics models that I had implemented before. Based on the discussion of certain regression models, the interviewer thoroughly asked questions about data cleaning, explanatory variables choosing and model modification. It was a nice progression since the interviewer guided me to take more practical problems into consideration in the process of model construction. (Tip- actively listen to the interviewer and be aware of the direction their conversation is heading, including tips they may give you.)

The second round of interview was an on-site visit to the company. During the second part of first round interview, the interviewer was interested in my interpretation of Logistic model application. I was also asked about basic SAS programming skills. Three interviewers interviewed me and gave me have a tour of the office. The SVP (Senior Vice President) of Risk Management introduced the team corporation of different groups in the division.

During the first part of the second round of interview, I had the opportunity to gather more details about the company’s business and culture, and had a nice communication with the interviewer about team contribution. All the questions were focused on the type of role that I could participate in the risk modeling team, and why I chose this company.

The Director and Modeler from the Risk Modeling team asked me to talk about some opinions on default probability model construction. Furthermore, they gave me concrete examples to show what kind of data that is usually dealt with and gave me chances to discuss practical techniques of data processing implemented by SAS programming. (Tip- be prepared to give  examples of your programming skills.)

The whole interview process was nice. The interviewers were willing to guide candidates to answer questions through practical problems solving techniques, come up with different solutions and opportunities for further discussion. The interview was a great way to communicate with professional people in the finance industry.


Have you had an interview yet? If so, was your experience similar or different? Share your thoughts and comments.

How I landed my dream job two months before graduation

by Samuel Busch, Financial Mathematics student- December 2013 graduate

As a soon-to-be graduate from the Masters in Financial Mathematics (MFM) program at North Carolina State University (NCSU), I thought it might be beneficial to prospective students to write a little bit about my experience in the program, specifically the opportunities the program has given me and what I have gained. Just in the past few weeks, I have landed my dream job working as an Actuarial Assistant for Allianz Life Insurance company.

So, how did I get here?

My undergraduate studies were in Actuarial Science and Statistics. I’ve always loved finding meaning in data and applying my mathematical skills in the “real world” in new and challenging ways. Risk management, insurance, and financial markets are subjects that continue to intrigue me. After earning my bachelors degree, I knew that there was a lot more that I wanted to learn about the mathematics behind risk and financial markets. What are the different kinds of exotic derivatives and how do they work? How do firms manage their exposures to various financial risks? What are the algorithms behind hedge funds? As an undergraduate, I wanted to know more about these questions; thus, I sought to increase my knowledge of quantitative finance through earning my MFM degree at NCSU.

I am so glad I decided to come to NC State and the MFM program for my graduate studies, as I give the program much of the credit for the success I have experienced in the past year and a half. The guidance and mentorship I have received from the MFM program director and the career services director have been extremely helpful and led to my amazing internship experience working as a programmer/modeler for an auto insurance company last summer.

Through volunteering for the program and attending program events, I have been able to meet industry professionals from banking, energy, insurance, risk management, and other technical fields.

As a student in the MFM program, I have received hands-on modeling experience in SAS and Matlab completing projects such as pricing exotic financial derivatives, and I have learned the fundamentals of asset pricing, stochastic processes (such as the stock market), and enterprise risk management.This education, along with my technical internship, has ultimately allowed me to secure my dream job where I will be able to merge my passions for risk management, insurance, and quantitative finance.

How did I “bridge the gap” between my education and finding the right job?

In short- networking through MFM program events and LinkedIn. As I gained experience, I updated my LinkedIn profile and joined groups relating to quantitative finance, actuarial science, insurance, and modeling.

Joining groups on LinkedIn turned out to be highly valuable for me. In fact, the day after I joined an actuarial / predictive modeling group, an actuary/director from Allianz Life posted a job advertisement to the group page and indicated that Allianz was looking to expand some of their actuarial positions. I jumped at the opportunity and applied on LinkedIn and through the Allianz web site. I also contacted the individual advertising the position through LinkedIn directly. This personal contact led to more personal contacts, which led to several phone interviews.

Eventually the phone interviews led to an in-person interview at the Allianz Life campus. During the interview, I highlighted my problem-solving, communication, and teamwork skills as well as my quantitative background, and my biggest selling point was the experience I had gained completing detailed and valuable programming projects for both the MFM program and my summer internship.

As a result of the successful interviews, I was offered and accepted a position as an Actuarial Assistant. In this role, I will work as a modeler and will have exposure to multiple business lines. I will be able to further improve my coding skills and knowledge of various financial and insurance products.

I hope my story helps to demonstrate the opportunities and skills the MFM program at NCSU provides and perhaps provides some encouragement to other students considering enrolling in the program. To new MFM students I would give the following pieces of advice:

1) Get involved with and volunteer for the MFM program

2) Utilize your program advisors and the Director of Career Services

3) Be very proactive with networking (LinkedIn)

4) Although you may not already have much quantitative experience, as you progress in your career, be aware of projects that highlight your analytical ability, communication skills, and teamwork, and use these as examples to leverage your skills to potential employers.