I'm really proud of navigating this very windy professional path, and not giving up until I got to where I wanted to be. I'm in my mid-30s, and only now I feel like I found my place in the world professionally.

Where did you grow up? Were you always interested in your current field?

I was born in Córdoba, the second biggest city in Argentina. As a kid, I lived in the US for four years while my dad was doing a postdoc in Denver, Colorado. That's why I always say that I cheat with my English. People say, "Oh, your English is so good." but I learned as a kid, which makes a huge difference. After those four years, we went back to Argentina and I lived in Córdoba until moving for my PhD.

My current field of work is data science and I'm in a very new type of position for the university, a Research Data Specialist.

We collaborate with researchers from any domain to implement data science techniques in their research. They bring the domain expertise and the research question, and then we help them use high performance computing, cloud computing, implement machine learning algorithms, program their algorithm in Python or in R, optimize or parallelise their code, data management… It's extremely broad.

I never knew it existed as a field, and that's probably because it actually didn't exist until very recently!

I was always interested in and always loved mathematics. I studied pure mathematics at university. But then it seemed a little bit too abstract and removed from the world, so I did a PhD in neuroscience, to get more into biology and real world applications.

It's been a very windy journey to find what I am really passionate about, which is collaborating with people to use mathematical and computational tools to answer their questions.

Does your role require lots of new learning? How did you find the move from maths to coding?

I'm learning things every single day. I hadn't actually used high performance computing before six months ago when I started using HPC for a collaboration.

I'm constantly learning new programming languages, because we're trying to meet researchers where they are. We are trying to help them create something that they'll be able to maintain and keep adding to as they move forward with their projects.

We do short term collaborations that run for three to six months. It's really important that researchers can take ownership of whatever we create and take it forward. We're constantly learning things and doing things that we know nothing about. But we learn as we go and work together to turn it into something.

Are you working from home? If so, how’s it going?

Yes, I am. I have been for a year almost already. Initially, I thought it was going to be harder than it was. Prior to COVID-19, whenever I worked from home, I would get distracted by cooking things or cleaning or doing things around the house that you never get the opportunity to do.

I set up an office. I have my routine and my desk. It's actually been great. I've really enjoyed having a that little bit of extra time that you save not having to commute.

I don't feel like it has affected really my relationship with my co-workers at all. We always work on these collaborations in teams.

Do you have kids/pets at home that are helping/hindering?

I do have a cat that we adopted in August 2019. It was perfect timing! She absolutely saved us during the pandemic. She kept us distracted and we'd check in on her and love watching all the new tricks that she learns. It's just been delightful to be able to spend a lot of time with her while we're both at home.

Her name is Meshi. It's short for meshgrid, which is my partner's favourite MATLAB function.

Meshi is a black cat with green/yellow eyes. Her head is visible amongst blue fabric.
Meshi, short for meshgrid, is named after a favourite MATLAB function.

My PhD supervisor had a kid and he named him Max, so we used to joke that he'd named him after his favourite MATLAB function. Adam, my partner, would say, "Oh, what am I going to do because my favourite MATLAB function is meshgrid?"

So then I thought 'Meshi' is really good. And we actually love the name and it works so well for her.

Meshi is black cat with green and yellow eyes. She is curled up on green cloth next to a small plant with green leaves.
Meshi the cat.

What projects are you working on now?

The main project that we're trying to round off at the moment is a bioinformatics project. It's the project that taught me how to use high performance computers.

Heroen Verbruggen is a researcher in the Faculty of Science at the University of Melbourne. He's really interested in eukaryotic mitochondria and chloroplasts that haven't really been studied. We downloaded about 50 terabytes of publicly available metagenomic data.

Metagenomic data is when you take a sample of soil or water, and you have no idea a priori which organisms are present there. Then you have to implement all these quite sophisticated mathematical algorithms to reassemble the genomes and work out which species were actually present.

We created a whole pipeline, a workflow, using something called Workflow Description Language, or WDL, to download the 50 terabytes, clean the data, trim it, assemble it, and work out the taxonomic classification of the species that are present.

Now all the processes are available for the group in the Faculty of Science to do their downstream analyses and try to find these chloroplasts and mitochondria - little snippets of genome - that they're interested in.

All of our collaborations run for between three and six months, but usually bleed over a little bit beyond six months, because it's really hard with research to anticipate how long things are actually going to take.

It's going really well. We had about 670 studies in total. So far we've processed about 570 of those, so we're only about 100 short. I'm really confident we'll be able to get to the end of this without any major issues.

What excites you most about what you do?

I love working collaboratively. And that's why initially I thought I didn't want to be an academic or a researcher, because it's so rare that you actually get to work in this way.

Normally, you have your own research question. And you have to fight others for funding to work on your project rather than other projects. I did leave academia for a few years, and I worked in education and public outreach. But then I really missed the technical aspects of coding and working with people, and talking to people about science and math.

Eventually, I did find a way back. I'm very hopeful about this very new position that doesn't really exist in many places yet.

It's actually perfect for me.

The other thing I really love about it is how I get to learn new things every day. I knew nothing about genomics before this project. And now, I'm not going to say I'm an expert, but I know a little bit about it, and I understand things so much better.

It's amazing how much you can learn from these absolute experts in their field, and by working across different projects every six months, I'm constantly learning new and interesting things.

What do you want people to know about the work you do?

What I do also benefits the research community. It's an extremely exciting new direction for universities and research institutes to explore. It takes so many years to build data science expertise. Within each discipline, there's only a small amount of people that develop these skills organically. There's not a lot of support to develop these skills, either, and there's no time and you have to focus on your grants and certain research questions.

A lot of people who are like me also get lost to industry and consulting, because if they like working collaboratively, and they don't see many opportunities to do so within academia, they're going to go to a consulting firm.

About 90% of the skills are the same across disciplines and they transfer quite nicely. If you know how to program in Python, you can make a Python script for biology or for humanities, or for the arts.

By having a centralized group that does these things, I think universities can actually save a lot of money in the end. And they can really elevate the quality of the research that's being done.

You can also bring so many interesting ideas from other disciplines. For example, something that's commonly used in physics, can suddenly be seen in a new way and applied to biology. We can see the parallels in the problem and bring techniques over to other fields, which can create really big breakthroughs.

What are you most proud of?

I'm really proud of navigating this very windy professional path, and not giving up until I got to where I wanted to be. I'm in my mid-30s, and only now I feel like I found my place in the world professionally.

I've moved across multiple countries and I've always been searching. Whatever I do, I recognize which aspects of it I like, and which aspects I don't like that much. Then I find a next step that takes me towards more of the things that I like, and less of the things that I don't like.

It's been a hard path to navigate from mathematics to neuroscience, and then to education and outreach, then public health.

And now I'm here in this role that brings together everything I've always liked, but I never knew existed. It was hard to get here, and I'm proud of myself for sticking at it and not giving up. I'm proud I didn't just stay in one place because it's comfortable. I kept searching.

My professional career has evolved. I did my undergraduate studies in Argentina, and then I did my PhD in the US. That's where I met my Australian partner, so then I moved to Australia. Every time you move to a new country, especially as an adult, it's so hard because you have no network whatsoever. Every time I'm trying to change areas and change my career a little bit, I know that having a solid network is so important for succeeding. So many jobs never get published in any platforms, but rather, are managed through connections and networks.

I'm really proud of having finally found my dream job.