Jonathan Whitmore

Following a postdoctoral position in astrophysics, Jonathan is a sought after speaker on computing and astronomy. He is excited by the application of machine learning and statistical techniques to industry problems and has developed novel data analysis techniques.

Jonathan has a diverse range of interests and is excited by the challenges and possibilities in the field of data science and engineering. He comes to SVDS after participating in the Insight Data Science Fellowship to prepare for transitioning from academic research into the tech industry. His Insight project was an art auction pricing prediction analysis. Before Insight, Dr. Whitmore completed an astrophysics postdoc at Swinburne University in Melbourne, Australia, where his research focused on trying to determine whether the physical constants of the universe have changed over cosmological times. This research sent him to world-class observatories to observe on the largest optical telescopes in existence. Further, he has a long-standing commitment to the public understanding of science and technology, most notably by his co-starring in the 3D IMAX film “Hidden Universe” which is currently playing in theatres around the world.

Jonathan received his PhD in physics from the University of California in San Diego, and graduated with a Bachelor of Science from Vanderbilt with a triple major in physics, philosophy, and mathematics.

Recent Posts

JupterCon notebook python

Themes from JupyterCon 2017

This past August was the first JupyterCon—an O’Reilly-sponsored conference around the Jupyter ecosystem, held in NYC. In this post we look at the major themes from the conference, and some top talks from each theme.

Exploratory data analysis in Python

Exploratory Data Analysis in Python

We summarize the objectives and contents of our PyCon tutorial, and then provide instructions for following along so you can begin developing your own EDA skills.

How to Navigate the Jupyter Ecosystem

In this post, we’ll be talking through a few tools that help make data science teams more productive.

Embracing Experimentation at AstroHackWeek 2016

Senior Data Scientist Jonathan Whitmore talks about experimentation and agility, based on his time at the unconference.

Jupyter Notebook Best Practices for Data Science

We present some best practices that we implemented after working with the Notebook—and that might help your data science teams as well.

Jupyter Notebook for Data Science Teams

Data Scientist Jonathan Whitmore has just released a screencast tutorial for Jupyter Notebooks.

Jupyter Notebook Best Practices for Data Science

We present here some best-practices that SVDS has implemented after working with the Jupyter Notebook in teams and with our clients.

Past Events


  • PyCon 2017

    Portland, OR

    PyCon is the largest annual Python conference, and will be in Portland, OR this year. Our team will be there, talking about exploratory data analysis. Let us know if you’ll be there, or come say hi at our tutorial.

  • TDWI Accelerate Boston 2017

    Boston, MA

    We’ll be in Boston covering a variety of topics—from running agile data teams, to visual storytelling with data. Let us know if you’ll be there, or sign up to receive all our slides.


  • Astro Hack Week 2016

    Berkeley, CA

    Data Scientist Jonathan Whitmore will be attending Astro Hack Week, please find him to say hi if you’ll be there.

  • PyData San Francisco 2016

    San Francisco, CA

    We’ll be at PyData, looking to learn more about how data scientists are using Python. Have a cool story, or questions of your own? Be sure to come find us.


  • OSCON 2015

    Portland, OR

    SVDS presents two sessions at the Open Source Convention: A tool-agnostic tutorial for those who want to elevate the look and feel of their data visualizations; and a talk that will explore some overall best practices for sharing IPython Notebook code within a data science team.

  • SciPy 2015

    Austin, TX

    Because of its flexibility, working with the Jupyter Notebook on data science problems in a team setting can be challenging. We present here some best-practices that SVDS has implemented after working with the Notebook in teams and with our clients.