How to prepare Risk Quant interviews?
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:
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
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.