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Timo moved to London to work in finance

Timo Seidl graduated from the master’s programme in Applied and Computational Mathematics in 2016. He now works as an associate at Napier Park Global Capital.

Timo Seidl
Master's programme in Applied and Computational Mathematics

Hi Timo, what are you working with at the moment?

I currently work at Napier Park Global Capital in London, an independent alternative asset management firm focused on investment opportunities in specialised credit. We invest in a wide range of credit products ranging from corporate bonds and loans, to credit derivatives and Collateralised Loan Obligations (CLOs), which are securities backed by a pool of corporate bonds and loans and where my focus lies. I joined Napier Park in April 2019 having spent two and a half years as a member of Goldman Sachs’ structured finance team, mainly focusing on arranging and structuring CLOs. I joined Goldman after graduating from KTH, having spent a summer interning there the previous year, something I can highly recommend to anyone interested in the industry as it gives unique insight into various teams within the divisions.

What might your regular working day look like?

On a regular day I would first catch up on some overnight news and make sure that I’m aware of any major events that may impact the financial markets and in particular our asset class. These days, with financial markets increasingly being driven by politics – such as trade wars, Brexit, etc. – there is always something to be reading up on. We often have team meetings in the morning at which portfolio managers provide updates on the portfolio and recent trends, or whatever else may be on their minds, and sector specialists (healthcare, telecommunications, retail, etc.) provide updates on anything noteworthy happening within their sectors. My role in the team can be described as a mixture of trading and portfolio management; speaking with traders from various banks and brokerage firms on a daily basis, sourcing and analysing investment opportunities and bringing them to the team for discussion and ultimately deciding whether or not to execute a trade. Structured credit products are traded over the counter, making constant communication with the various trading desks a key factor in gaining as much information as possible so that no opportunities are missed. The rest of a typical day might be spent developing tools and reading market research that helps the team analyse opportunities and make investment decisions.

Why did you choose this programme at KTH?

In my case, the decision to move to Stockholm was mainly for personal reasons; however, KTH’s programme in Applied and Computational Mathematics seemed the obvious choice over other programmes in the field given the broad range of courses offered and the clear focus on industry-related course content and projects. Having studied pure mathematics for my bachelor’s degree, that was certainly an aspect I appreciated a lot. In addition, students were encouraged to collaborate on their master’s thesis with companies that would not only allow them to build important relationships with mentors in the industry and perhaps even result in a career start, but also provide a good idea of what a practicable application of the degree might look like.

Did you acquire any insights during your studies that have been particularly useful to you?

I would say that what helped me the most was not one particular subject but rather learning how to approach technical, quantitative problems, often involving different datasets, and develop analytical skills. While I don’t use the concepts I encountered at KTH on a daily basis, the theoretical knowledge I gained in financial maths, regression analysis and machine learning certainly helped me to not only get a job in the industry but also to subsequently pick up new technical concepts quite quickly. Having said that, financial concepts such as option theory are certainly a prerequisite for working in a technical role within finance and from time to time I do also use statistical methods (such as regression analysis or some fairly basic machine learning methods) that I first encountered at KTH when looking at different types of data.

What were the best aspects of your studies at KTH?

The best aspect of my studies at KTH was that the programme was very dynamic and allowed me to take elective courses from various fields across financial maths, statistics, optimisation and machine learning. This is also the main message I would give to prospective students applying to the program: do not follow one track too closely but pick subjects from as many different fields as possible. Even if at the time you feel certain you want to do one particular thing, this may change in the future; in which case, knowledge and skills you may have picked up in other fields will be invaluable. I also thought that the general atmosphere at KTH was very collaborative and that the university was full of very smart, curious students, while lecturer’s doors were always open for students seeking help or just wanting to discuss some topics.

What is your best memory from your time at KTH?

I don’t have a single best memory from my time at KTH; however, I am most grateful that it allowed me to get to know so many new international and Swedish friends, to live in such a wonderful city and get to know the culture a bit better while being able to enjoy a top-class education. The long summer nights when the sun barely sets certainly also left quite an impression!

What are your plans for the future?

For the time being I want to continue focusing on my current role, using my financial and technical skills to continuously increase efficiency in my workplace through automation. It might also be interesting to apply machine learning concepts to credit markets, which are lagging considerably behind equities and foreign exchange markets in terms of innovation. I will see what the future brings; however, I am generally of the view that data will continue to increase in importance across most fields and that that is a trend I would like to be a part of.