Dear NYT,

Thank you for considering me for the position. I believe I'm the sort of person who can contribute to the NYT's mission.

I have been working in quantitative social sciences for about fifteen years now, ever since getting a PhD from the Social Science program at Caltech. Throughout, my goal has been improving the public good via better math.

With that in mind, most of my résumé is government service. For example, the project I am currently working on is improving the method by which taxpayers are chosen for audit. Better math pays off: Even a one percent gain in efficacy would generate about $140 million in tax revenue, and algorithms today can measure fairness in ways that were impossible in decades past.

But there are a lot of different approaches to math for the public good. In government service, and in direct policy advocacy at Brookings, I have generated technical works for a small audience of policy makers. For example, my latest is this academic analysis of U.S. domestic migration patterns, currently under review at a journal [generated via Hadoop→Hive→Spark→Python→LaTeX]. But addressing the public at large is also essential. Research reports using agent-based models have impact in one direction, and agent-based models for non-technical urbanists have impact in another [via C→Gnuplot]. Writing a short piece for Scientific American on interpreting scientific studies—an op-ed about 12-dimensional spheres!—has been a highlight of my year.

This is just a cover letter, nothing flashy, but if you'd like a demo please have a look at 1040.js, a page that goes beyond "doing" your taxes to following the flow of the calculation and understanding how the final number gets calculated [via tax form DSL→D3]. It is low-tech by NYT standards, but this little spare-time project has gone far beyond my expectations—even researchers at IRS have told me they learned from it.

The evolution of data journalism over the last few years has been wonderful to see, and has become a whole new avenue for math for the public good. I believe the skills that I've developed in diverse contexts would be a great fit for the NYT as it blazes this new trail.

Regards,


Ben Klemens