Talks and conferences

Over the past few years I have been doing a lecture tour, where I help people understand data science in industry. This includes helping students prepare for getting jobs, businesses strengthen their offerings, and technical experts learn new methodologies. Below are a selection of my materials.

Catch me @

  • July 2018: SIAM Conference on Applied Mathematics Education
  • June 2018: Cascadia R Conference
  • June 2018: PIC Math workshop
  • January 2018: Data Day Austin

For math students and professors

Finding math jobs in industry

Everyone keeps saying that there are tons of jobs for mathematicians, but if you search on job sites for "mathematician" all you get are teaching jobs. There are special words that companies use to describe math jobs such as: analytics, operations research, and data science. In this presentation I discuss what steps students can take to make them great candidates for industry, how to find the jobs that have the interesting math problems behind them, and how to answer the age old question: should I go to grad school?

For people who use R professionally

Using R on small teams

Doing statistical analyses and machine learning in R requires many different components: data, code, models, outputs, and presentations. While one person can usually keep track of their own work,as you grow into a team of people it becomes more important to keep coordinated. This talk discusses the data science work I did as a director of analytics, and why R was a great tool for our team. It covers the best practices we found for working on R code together over many projects and people, and how we handle the occasional instances where we must use other languages.

For people who make products

Tweet Mashup: the rise and fall of a meme

I never expected my side project,, to immediately explode in popularity the moment I launched it. The site wasn't written to scale, nor was I emotionally prepared for it. This talk covers how I had to duct tape the site together to keep it working, and how quickly it entered and exited the public conscious.