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Nordea Markets to STEM grads: We want you

14-10-2021 09:00

As financial markets become more digital and data-oriented, so-called "quants" and people with backgrounds in science, technology, engineering and math (STEM) are more in demand than ever. Nordea Markets representatives recently met with STEM students at Lund University to raise awareness of the opportunities.

When Lars von Moos earned his Ph.D. in solid-state physics back in 2014, he never imagined working in a bank. However, after five years as an engineering consultant, modelling district heating and water networks in city areas, he craved more work with data science and computer programming. He applied for a so-called “quant” role in Nordea Markets, and today he works with financial modelling, data analysis and machine learning in the e-Trading team.

“I really like the diverse and challenging tasks I face every day in my current work. Learning and personal development are highly encouraged to help you solve tasks in new ways,” he says.

Lars is one of 15 quants on the e-Trading team and around 60 across Nordea Markets. As the world becomes more digital, so do financial markets, which makes them more competitive and fast-moving. This requires banks to have more sophisticated data and mathematical models as well as high-performing technology, says Daniel Schiermer, head of e-Trading at Nordea Markets.

“Quants and people with STEM (science, technology, engineering and mathematics) backgrounds are key to making this a reality and helping us stay competitive in the markets and relevant to our customers,” he says. However, the first challenge is getting this point across to STEM students and making them aware of the opportunities.

Life as a quant in Nordea Markets

To do just that, Daniel, Lars and two other members of the e-Trading team recently participated in the virtual Quant Fair at Lund University in Sweden. The event, arranged by the STEM division of the Lund University Finance Society (LINC), gathered 30 students to learn more about how they can apply their skills in finance.

One student attendee, Johanna Lindholm, a double-major in Engineering Physics as well as Industrial Management and Engineering, was excited to see the role of STEM grads in banks being advertised more widely.

“At least among my fellow engineering friends, finance is probably not the first thing that comes to mind as a profession. But it’s great to see that you can apply a lot of the really cool technology, machine learning and computer science, and that there’s a place for STEM graduates as well,” she says.

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It’s great to see that you can apply a lot of the really cool technology, machine learning and computer science, and that there’s a place for STEM graduates as well.

Johanna Lindholm, STEM student at Lund University

The quant toolbox

Lovisa Thordin, another Nordea Markets representative at the Quant Fair, told students that she didn’t know what she wanted to work with when she was studying Engineering Mathematics at Lund. She reached out to Nordea when she embarked on her Master’s thesis, and later landed a quantitative/data analyst role in Nordea Markets.

“The job is a great mix between math and business. I appreciate being close to real-life problems and using the skills I learned at university,” she said.

The presenters outlined three basic career paths: quant analyst, quant trader and quant developer.

Malthe Kirkbro, another Nordea presenter with a background in software development, provided the quant developer perspective. He described his work taking models and putting them into production as very “result based.”

“You can immediately see the fruits of your labour in the P&L (profit and loss). I like working with these close-to-the-metal computer science problems that come down to the microsecond. It’s one of the coolest places to work in tech these days,” he said.

Getting your hands dirty with machine learning

To bring theory to life, the Nordea Markets quants presented two real-world examples from their work. Malthe described the use of modelling to figure out the current market prices for a given currency pair in the FX (foreign exchange) market, while Lars gave an example of using machine learning and “clustering” to figure out which customers are a good match for a new Nordea automation product.

“There are many ways to get your hands dirty with machine learning,” Lars said.

Amanda Ramirez, a Lund student who co-organised the workshop, says she was excited to see machine learning concepts applied in practice.

“Machine learning is a hot topic you read about in a lot of research papers. It was great to see that it can be used to make actual business decisions,” she says.

Data science and machine learning are trends that aren’t going away anytime soon, according to Daniel Schiermer. He notes there are many examples where they can be key enablers, for example, with the automation of manual processes or making daily work more efficient by processing and enriching vast amounts of data, adding:

“Data is opening up a lot of potential for us, and we need quants to unleash that potential.”

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