Research coordinator at the Institute of Psychology, University of Oslo

Matteo Botta works as a data manager for the SIBS-RCT project, a randomised control trial (RCT) project that investigates mental health and quality of life of siblings and their parents, in families where there is a child with a chronic disorder. He is responsible for the data processing with respect to the quantitative part of the project. 

 ¨C Through the master programme in International Community Health, I acquired broad and solid research methodology fundaments and analytical skills, Botta explains.

These skills are keys to understanding the SIBS-RCT project he works on:  
?    the methodology behind it
?    how it is designed
?    how the data is collected and managed
?    how it can be made serviceable for the data analysis process.

What is the most exciting thing about your job?

 ¨C  What I love the most about this job is the flexible working hours and the possibility to work remotely. Besides this, it makes me feel good to know that I have an important role in the project. Data would be impossible to analyse without the necessary back office work of cleaning, linking, and harmonisation, he says.

How is a typical day at work? 

 ¨C  I work mostly remotely, and I have total freedom to manage my working hours, apart from the scheduled meetings. When I physically go to work, I enjoy very much sharing an office with PhD students. The work environment at the University of Oslo is extremely good and intellectually stimulating. I could not ask for a better environment.

How did you get the job? 

 ¨C They needed someone who had a good understanding of the challenges behind an RCT project, its data collection and processing. So I applied for the job.

What are your best advice?for students who want your type of job?

 ¨C The master programme in International Community Health was certainly preparatory for this position. It allowed me to develop all the competences I need; however, you also need to have an analytical mindset, be systematic, and pay close attention to details. Further, find time to attend to courses on data management planning, coding in R or Python, for example, and data visualization, as well as becoming a competent spreadsheet user.