The data series: Interview with a data scientist in the financial industry

The shortage of data scientists is becoming a serious constraint in some sectors. What do you think needs to change to help increase the number of data scientists entering the profession?

As data science tools and packages become widely available, I believe it becomes easier to train people with no background in data science but a strong domain knowledge to use data science techniques. For example, using a Google Vision API doesn’t require advanced data science skills but can help solving real business issues and deliver value.

What is the biggest impact Covid-19 has had on your line of work?

The projects I work on tend to involve many different parties which makes coordination and communication important. The health crisis definitely created a lot of disruptions at the beginning but I feel like people have now adjusted well to the “new normal”. This is the new business as usual.

Do you think big data will fundamentally change our approach to the next pandemic?

I think we can definitely build tools to identify issues earlier and prevent spreading through accurate modelling of contagion vectors and clusters. The economic damage caused by this crisis clearly justifies investments in such tools. However, I am afraid that international politics will never allow for a perfect technology driven pandemic response.

What excites you most about recent developments and the future of data science?

What excites me the most is the implementation of data science techniques to traditional businesses that do not necessarily come to mind when thinking about technology applications. Self-driving cars and super accurate voice recognition are very exciting but it is also exciting to see the scale of value we can provide by modernising how traditional industries operate. I am in general very excited by decision making tools that leverage human experience and domain knowledge with advanced data science analysis and forecasting tools.