How did you become interested in the business & data analytics field and how did you end up in your current work position?
When I applied for the Master’s programme, Business Analytics was a relatively new major and I did not know much about data analysis or programming. But all this new knowledge was what has kept me interested in the field. Data analytics is where you can apply theories and technical knowledge in solving real business problems. Also the career prospectives of this field are very high - good data analysts or data scientists are very much in demand today.
During the last year in my Master’s studies, I worked in Business Analyst trainee positions at two companies in totally different industries. I learnt how those companies were leveraging their data and data analytics for making important business decisions. From there I knew what kind of technical skills might be useful and tried to improve myself in those areas.
Finally, I got accepted to Nordea’s Graduate program before finishing my Master’s thesis and since then have been working as Data Analyst.
You work as a Customer Insights Analyst at Nordea. Could you describe your typical workday in your job and typical work assignments?
As a Data Analyst at Nordea, I work in a centralized team and collaborate with different stakeholders from both business and IT side. Usually the requests for data analysis come from business side, namely management team, and sales and marketing teams.
Work assignments can be different topics, for example, creating a target group for the upcoming marketing campaigns, analyzing certain customer segment’s behaviors, or analyzing credit portfolio performances.
Like many other big companies, the data landscape at Nordea is very complex, so often data analysts would have to spent a lot of their time identifying and gathering the right data for a project. Therefore we need to work closely with data engineering teams to ensure that the data assets are delivered and properly maintained. Some cool projects could involve developing and maintaining machine learning models.
There is a wide range of applications for different purposes in our data analysis toolbox, but the ones I use the most nowadays are Python, Hive SQL, SAS and Power BI.
What is your advice for current foreign students related to job hunting in Finland?
To make yourself standing out among other candidates, especially for a position that does not require Finnish language, it’s important that your application has a focus, for example showing your goals and interests, and how your skills match with the applying position.
A good way to do that is to highlight your personal projects which are most related to the job, whether they are course projects from school or from an online platform such as Coursera or Udemy. In my experience, employers highly appreciate a candidate who has an interesting project portfolio that shows off his/her data analysis skills. This applies also very well to the internship or entry-level jobs when students do not have much working experience.
Besides, I would recommend our students to actively attend the networking events organized by our school to learn more about the alumni and the companies they are working for. Chances are very high that you will work with some of your Aalto fellows in the future!
What would you do differently in your studies?
I would try to do more personal projects besides the core studies, something like learning how to improve the data visualization, or maybe building prediction models using text data. They do not need to have great results but I might have had more fun and learnt faster this way.
Read more about Tung Hoang’s career path on LinkedIn: https://fi.linkedin.com/in/httung!
Check the events and trainings organized by the School of Business Career Services (requires an Aalto login).