From Agronomist to Data Scientist: My Journey into the World of AI and Data Science

Please tell us your name, what you currently do, and where you work:

My name is Maria Carolina. I'm a data scientist with 4.5 years of experience, currently working at a tech company in Brazil.

How did you get into Data Science?

My journey to data science is unique, I guess. I began my career as an agronomist, completing advanced degrees including a master's and doctorate, and worked as both a postdoctoral researcher and university professor (did not like teaching undergrad very much though).

When I first learned about data science through international websites and blogs, it was still an emerging field in Brazil, with very few local job opportunities. So that seemed pretty impossible to me. But somehow, despite living far from the country's major financial centers where most tech jobs were concentrated (and I could not move out of state for a job), I managed to break into the field. My agricultural background was the main reason, I joined a company focused on agribusiness.

What does your day-to-day role involve?

My role varies depending on current projects, but research is a constant and significant component. Some tasks require several days of research before any coding begins (which I really enjoy).

What technology or programming languages do you frequently use to get your work done?

I primarily use Python, which is standard across our team. Given our focus on agribusiness, I also work extensively with GIS software, particularly QGIS (a big fan of this tool), and SQL.

What do you like the most about your job?

The research-intensive nature of my work is what I enjoy most. It feels like an extension of my academic research background but with the added satisfaction of developing practical products. I have to stay current with the latest research, state-of-the-art developments in the field, statistical analysis, machine learning techniques, and efficient programming practices.

What is something you think people do not know about data science or data scientists?

I understand that there is a wide variety of data roles. Even though data scientist is just one of them, there are many different profiles that a data scientist can embody, depending on the company, client, and projects. I don't know if everyone realizes the diversity of possibilities that this role provides - and of course, how much it evolves and seems to change by the year. But I believe that any data scientist should be very interested in research and learning, and I say this in addition to knowing how to run models for example (which of course also requires a lot of study).

While technical skills are crucial, a fundamental curiosity and passion for research and continuous learning are essential traits for any data scientist.

What are some trends in data science that you’re particularly excited about?

I'm particularly excited about AI's evolving role in data science (although at the same time, I feel the need (daily) to continue learning much more about what we already call "traditional"). While it began by streamlining basic tasks, I believe we're moving toward more sophisticated and complex applications of AI.

If you weren't a Data Scientist, what would you be doing?

I would probably be in a research position (if I managed to, of course), as I'm deeply passionate about the scientific process - forming hypotheses, developing methodologies, testing assumptions, and documenting findings.

What are 3 quick ways for someone to get into Data Science and land a job within a year?

For aspiring data scientists, my advice is to:

1. Develop a genuine interest in continuous learning and problem-solving (NEVER ends….and maybe that's very good)
2. Focus on understanding underlying concepts and their connections (understanding the reasons behind the things!)
3. Balance your studies between statistics, programming, and business domains (no one knows all…)