How to prepare Risk Quant interviews?

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I am currently an undergraduate junior at a target school majoring in engineering. I will be interning at a BB risk department summer (non-quant role), where I will be working on things like initial margins for non-cleared OTC derivatives.

Ultimately, I am interested in more quanty risk roles. I have taken courses like statistics, probability, econometrics, data structures and etc. How am I supposed to prepare interviews for quant roles in risk department at investment banks? How much should I study programming and other stuff?

These are the sorts of risk quant roles that I am very interested in:

1.
CIB - Quantitative Research - Equity Derivatives – Associate – London Position: role in the Equity Derivatives Quantitative Research team - focusing on the quantitative optimization of trading Description: work in close collaboration with Flow & Exotics Equity Derivatives traders to optimize quantitatively trading operations. This involves working on risk management (Delta and Vega hedging…), derivatives portfolio optimization, systematic relative value analysis, trading signals & strategies and improving the efficiency of execution… Practically: perform research, build models, tools and processes, support the trading desk on these fields. We are looking for an Associate level quant for this versatile role which mixes classical derivatives quant skills with statistical modelling and optimization. Autonomy, good communication, strong motivation and curiosity towards derivatives trading and equity markets are critical for this role. Qualifications Skillset: • Derivatives: excellent knowledge of pricing and risk management theory (Black & Scholes…), vanilla options and volatility products (variance swaps, VIX futures and options, stochastic volatility models …) • Statistical modelling & optimization: standard techniques, machine learning. Linear, convex & conic optimization… • Strong coding background: ability to work with large amounts of data and comfortable with technology, proficient in Python and relevant quantitative packages (numpy, pandas, scikit…), good knowledge of C++ JPMorgan Chase & Co offers an exceptions benefits programme and a highly competitive compensation package. JPMorgan Chase & Co is an Equal Opportunity Employer



2.
The Market Risk Quantitative Research Group at JPMorgan Chase is responsible for enhancing the VaR modeling capabilities and process as well as providing quantitative support to Market Risk end-to-end, from methodology to delivery. We partner with desk aligned Quantitative Research, Market Risk Coverage, Technology, Model Risk and Development, and Product Control teams. The MRQR team is currently looking for an associate level candidate to work on the following: • Support the BAU (Business As Usual) tasks that emerge on a daily basis for Credit VaR and SVaR for MRQR. • Generation, analysis, and automation of periodic commitments such as parameter recalculation and exposure monitoring for Credit VaR Methodologies. • Perform the analysis necessary to address Action Plans (AP) arising mostly from model review and audit groups. Qualifications • This requires a quantitative background at a Master’s level or equivalent in a hard science (maths, statistics, engineering, or science), and experience or proven interest in financial industry or model development (VaR, stress, or derivatives pricing models). • The job requires time series analysis, statistics, familiarity with VaR, Python, Excel, and SQL. • Keen interest in internal policy and governance and external regulatory rules and supervisory guidance • Strong communications skills - Verbal and Written • Team work oriented - Active collaborator and self starting individual • Strong organizational and project management skills. Risk & Control mindset • Work well under pressure with commitment to deliver under tight deadlines • Detail Oriented JPMorgan Chase is an equal opportunity and affirmative action employer Disability/Veteran.
 
The roles you list are quite different, and by the job description have very different requirements as to previous experience and skillset.

The first is a front office quant role, and the job description covers pretty well what is expected of you: a couple courses worth of stochastic calculus and prior experience in equities (so in practice someone who's interned at a bank as an equities quant), and an interest in using "nontraditional" tools, i.e. statistics. Good Python required, but when it comes to programming it is probably the basics of C++ that the interview will test.

The second role is a middle office quant, and by description is less mathematical and also uses less technical tools: Calculating VaR, not requiring much in terms of previous experience or programming ability. In this role you probably get to see a bigger picture than in the former, as you'll be less aligned to a specific desk.

Regardless of the role it would be good to know the basics of C++, but from your description what you really seem to missing is some more rigorous math course into derivatives pricing. So do a course or two (i.e. an MFE or equivalent) in stochastic calculus would be my recommendation.
 
The roles you list are quite different, and by the job description have very different requirements as to previous experience and skillset.

The first is a front office quant role, and the job description covers pretty well what is expected of you: a couple courses worth of stochastic calculus and prior experience in equities (so in practice someone who's interned at a bank as an equities quant), and an interest in using "nontraditional" tools, i.e. statistics. Good Python required, but when it comes to programming it is probably the basics of C++ that the interview will test.

The second role is a middle office quant, and by description is less mathematical and also uses less technical tools: Calculating VaR, not requiring much in terms of previous experience or programming ability. In this role you probably get to see a bigger picture than in the former, as you'll be less aligned to a specific desk.

Regardless of the role it would be good to know the basics of C++, but from your description what you really seem to missing is some more rigorous math course into derivatives pricing. So do a course or two (i.e. an MFE or equivalent) in stochastic calculus would be my recommendation.


Thank you so much for your reply. I am more interested in the "middle/back office quant" than the "front office quant". I haven't taken any stochastic calculus course, but I have taken three actuarial exams (P, FM, and MFE) where I learned options pricing models(Binomial, Black-Scholes, and their underlying models such as Brownian motions, interest rate models such as black derman toy models etc). I guess I can learn the basics of C++ this summer. What else do you think I can do this summer to prepare for the latter role? (I am an undergraduate junior and will be recruiting for full-time roles in the fall semester).

Thank you .
 
Thank you so much for your reply. I am more interested in the "middle/back office quant" than the "front office quant". I haven't taken any stochastic calculus course, but I have taken three actuarial exams (P, FM, and MFE) where I learned options pricing models(Binomial, Black-Scholes, and their underlying models such as Brownian motions, interest rate models such as black derman toy models etc). I guess I can learn the basics of C++ this summer. What else do you think I can do this summer to prepare for the latter role? (I am an undergraduate junior and will be recruiting for full-time roles in the fall semester).

Thank you .

By MFE I meant a Master's in Financial Engineering. Sorry for the confusion, I did not realize there was another meaning to the term. Indeed the role does "require" a master's, so it is probably difficult to get an interview for a full time position if you just got your Bachelor's degree.
 
Thank you very much. What do those acronyms stand for? I also thought that programming knowledge is essential to be a risk quant. Is it usually the case?
"Programming knowledge".

Risk Quants typically don't program, they script. They will often put together scripts that the risk developers will either:

1. Rewrite in Java or C in the "black box" risk machine
2. Insert the quant's script directly into their code

Focus on the math and finance you would expect on any risk interview but also be prepared to be challenged on:

1. R
2. Python (more on buy side)
3. VBA
4. SQL
5. Matlab (some firms)

1, 3, 4 are absolutely essential to know for a risk quant position.
 
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