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CQF alumnus, Michele Maio, is a Risk Trading Quant at ING in Amsterdam. He has a background in theoretical physics at PhD and postdoc level and started working in quant finance in 2014. Since then, he has worked as a software engineer, modeler, risk analyst, and quant developer in different institutions (mostly banks) and in various areas, such as ALM and trading. He joined ING’s team of Risk Trading Quants in December 2020. We caught up with Michele to find out more about his typical working day.
I work at ING as a Risk Trading Quant within the Modeling Department. My focus is on the estimation of Counterparty Credit Risk (CCR) and the methodology for various Value Adjustments (XVA) for the bank’s trades portfolio. We implement all the CCR and XVA models that are in our scope into our internally developed C++ software, which computes the relevant risk metrics via calibration and simulation of correlated stochastic processes. My role also involves liaising with relevant stakeholders, setting up activities and infrastructures for the whole CCR and XVA team, and coaching more junior team members.
Below, is my typical working day as a Risk Trading Quant.
My day starts with a catch up with my team. This takes place either in person in the office (two days per week) or virtually when working from home (three days per week). With a warm cup of coffee in hand, we review the tasks for the day, refresh our planned task list with any additional requests, and follow up on any pending items.
During this part of the day, I normally spend time working on my own tasks or collaborating on project tasks with my colleagues. Examples of a typical pieces of work include implementing new model features into our library, analyzing the best model options to propose for production, and preparing data that the entire team will use later. The work is usually technical and can be focused on either model development or team infrastructure.
One more concrete example of my typical work is a project I worked on recently. We had to build out and extend our internal library with new products. My tasks were all related to the pricing of these products, to make sure that MTM’s and exposure profiles were calculated correctly. At the same time, I also supervised my junior colleagues as they worked through the definition and selection of market scenarios and on pricing performance speed-up.
Time for a lunch break. If I am working from the office, I usually join my colleagues in the quest for food and we typically end up either at the bank cafeteria or in a small shop in the neighborhood. If I am working from home, I like to take a short walk to recharge while having a snack.
I have project meetings with my team members, either in person or online, to discuss progress and to review, support, and help plan their work. Sometimes we also have meetings with the larger team to align on internal planning and way of working, or to attend internal trainings and seminars.
If time allows, a short coffee break is the perfect opportunity to catch up with colleagues in a small setting while taking a break. This is even better if I am in the office and can visit the cafeteria where the coffee is quite tasty, and the atmosphere is relaxed.
There is still normally work to be finished at this time to complete the daily tasks that were planned in the morning. Sometimes it is necessary to reach out to other departments to align on priorities. Typically, we discuss modeling challenges with the Front Office, data requests with the Data Team, policies and regulations with the Model Validation team, and technical infrastructure with IT.
It is time to close the day by preparing a to-do list for the next day. After work, I normally exercise or engage in social activities that help me recharge. Once a week I join our team drinks, often accompanied by dinner. Whenever I can, I always enjoy walking around the city center and relax at home.
If you are interested in becoming a lead software engineer, explore the CQF Careers Guide to Quantitative Finance. Learn more about the skills needed and average salary you can earn in North America, Asia, and Europe for key career paths in quantitative finance.