Erika

What were you researching before you started as a Science Policy Fellow?

My research career focused on understanding how our body’s defence system (the immune system) could sense and respond to harmful events such as an influenza virus infection. A deeper understanding of how these defence systems are co-ordinated may allow us to develop new therapeutic strategies for treating pandemic infections that can arise and spread very quickly between humans.

What policy area are you working on through the Science Policy Fellowship Program?

I work in the Department of Employment, Skills, Small and Family Business and have landed deep in the data analytics space, where I can apply new analytical insights to better understand policy implementation. I am also contributing to our working understanding of machine learning frameworks, which is an extremely interesting and new area for policy development.

How has your research background helped you contribute to policy development?

A transition from biology to understanding government employment services might sound like a radical change, but research skills such as critical thinking, communication and scientific hypothesis testing have all helped me to make a smooth transition. In research, the creative freedom to take on and manage new projects, collaborate with other scientists and communicate your findings means that you can develop very valuable skills, like quickly understanding and communicating technical concepts to a wide audience, designing workflows and managing project risks and outcome uncertainties. My previous programming skills (in R) and bioinformatics work experience have also been an unexpected bonus in my current role. 

How has the program changed your career aspirations?

I feel very lucky to work, now permanently, in my team, where there is a lot of support for people to pursue further learning (in statistics, programming and policy design). I am deeply interested in the machine learning and artificial intelligence space from a policy implementation perspective and hope to keep contributing in this area. I also think that there are tremendous gains in coupling new data analytical insights to evidence-based policy decision making, and I would like to keep contributing actively to this area in the future.   

What is your favourite part about working in a policy role in the Australian Public Service?

I have two favourite aspects. The first is that I can constantly apply my critical thinking skills in new ways and keep improving my programming and machine learning knowledge. The second and equally important aspect is that I get to work with talented and supportive people and can always access the amazing support network of current and past Science Policy Fellows.