Danielle Navarro

Data scientist, developer, technical writer, and educator

Employment History

Developer Advocate, Voltron Data (2022)

Reduced barriers to adoption for developers using Apache Arrow
Developed and delivered training material for technical audiences
Improved user experience for developers in a complex software ecosystem
Worked with software engineers and communicated community feedback
Contributed code to improve software usability for users and developers
Built a trusted profile to engage with community members on social media

Associate Professor (2012-2021)

Associate positions are senior (tenured) roles with multiple responsibilities. I held appointments at the University of Adelaide (2012-1015) and the University of New South Wales (2016-2021). Core responsibilities are listed below:

Project management, finances, and team leadership
Leadership roles in the broader scientific community
A/B testing and advanced experimental design
Data analysis, statistical modelling, and machine learning
Curriculum development and delivery for technical subjects
Grant and report writing, and publishing scientific research
Research software engineering (mostly in R and Javascript)

Lecturer/Senior Lecturer, University of Adelaide (2006-2011)

Australian equivalent of tenure-track academic positions in North America. My duties were similar to those listed in the previous section, at a more junior level.

Postdoctoral Researcher, University of Adelaide (2004-2005)

Build Bayesian nonparametric statistical models of human cognition
Research software engineering, mostly in Matlab/GNU Octave
Serve as primary data analyst for complex statistical analysis tasks
Take a primary authorship role in writing scientific papers

Postdoctoral Researcher, Ohio State University (2002-2004)

My responsibilities at Ohio State University were similar to my later responsibilities as a postdoctoral researcher at the University of Adelaide above.

Education

Ph.D. in Psychology, University of Adelaide (1999-2003)
Bachelor of Social Science (Honours), University of Adelaide (1994-1998)

Content creation

blog.djnavarro.net
Data science blog with 108k page views in 2022

learningstatisticswithr.com
Statistics text with 246k page views in 2022

arrow-user2022.netlify.app
Short course on big data workflows in R with Apache Arrow

Academic roles

Academic careers are not organised into the same categories we typically use to describe industry roles in tech, so it's helpful to unpack it a bit. In practice, a tenured academic functions like a small business owner operating in a broader regulatory context, and usually has several part-time career paths that evolve in parallel.

Editorial career

Scientific editors are senior members of the academic community who review submissions for scientific quality, breadth of interest, and readability. To do this job well you need to have broad mastery of the academic discipline involved, stellar writing skills, and the ability to delicately negotiate conflicts among authors and reviewers. During my academic career I held editor roles at these journals:

Science. science.org
Behavior Research Methods. springer.com/journal/13428
Cognitive Science. onlinelibrary.wiley.com/journal/15516709
Open Mind: Discoveries in Cognitive Science. direct.mit.edu/opmi
Journal of Mathematical Psychology. sciencedirect.com/journal/journal-of-mathematical-psychology

Teaching career

Academics are expected to be teachers, naturally. The complete scope of my professional education career is extremely broad, but I'll note a few highlights that are relevant in the context of tech roles:

I've developed content for teaching large data workflows to data scientists: arrow-user2022.netlify.app
I've taught statistics to social science students and other beginners. I wrote a book about it here: learningstatisticswithr.com. This teaching won awards from the university and from professional societies, and the book has been translated into other software systems (JASP and jamovi) and other languages (French and Japanese) by the broader community.
I've taught statistical learning, artificial intelligence, and computational theories of human cognition to computer science students. Example course materials: compcogsci-3016.djnavarro.net. The course covers probabilistic reasoning, supervised and unsupervised learning, hidden Markov models, probabilistic grammars, and introductory reinforcement learning.
I've taught the psychology of language, decision making, reasoning, and other aspects to human thought and behaviour.

Managerial and organisational career

I've chaired research and other committees in academic departments. This is a senior role that requires people management skills but also requires an understanding of local political sensitivities, domain knowledge, policies and regulations, and so on.
I ran my own research group for 15 years, recruiting my own personnel, mentoring them through their junior careers and helping them find them senior roles after they completed their Ph.D. work in my group. In this role I secured funding to support my team, managed the budget over long periods (often in uncertain economic conditions), and developed local administrative processes to ensure stable team governance over the years.
I've been a senior participant in several multi-organisation multi-million dollar research bids that have necessarily involved considerable negotiation and balancing of interests.

Research and technical communication

I have written several acclaimed books, including one of the most successful statistics textbooks in R (learningstatisticswithr.com) and one of the most popular data visualisation books in R (ggplot2-book.org).
I've written over 100 scientific papers. They aren't exciting to document in a résumé because scientific work is technical and favours precision over marketing value, but you can find full-text open access manuscripts here: papers.djnavarro.net.
I was awarded the 2007 William K. Estes Early Career Award by the Society of Mathematical Psychology: what it means in practical terms is that I am skilled at studying human thought and reasoning, developing mathematical and computational models that simulate those processes, and have expertise on the relationship between human thought and machine computation.
I've won numerous other awards for my research papers, including best paper awards in computational linguistics, spotlight papers at the prestigious NeurIPS machine learning conference, and best paper awards in mathematical psychology journals.