R in Finance 2016
Review of R in Finance 2016 conferenceread more
A few months back I wrote about my experiences trying to hire a data scientist. It took some amount of work on our part. When we finally found the right candidate, our parent company told us that there wasn't actually any money to pay a candidate. This came as rather a surprise to all of us at our three person startup. This was the first indication that the wheels were coming off the bus, and two months later, we were all laid off and the company dissolved. Within just three months I went from hiring to scrambling for a job. Would I follow my own advice for job candidates? What's the startup climate like? Is it easy to find a job in the field?
I decided to make of habit of (nearly) always writing a cover letter, although I quickly settled on two or three templates of cover letter, depending on the job function and industry. I found the address of each company and included it in the letter, mostly to confirm that the office was in the city of San Francisco. When I submitted an application, I would save the letter in my (private) applications repo on github, with a message. I had been warned by a friend who works in HR that cover letters were ignored in her office. In my experience, a cover letter, even a somewhat generic one, set apart casual applicants from the serious candidates.
I also made the not uncontroversial decision to send out my lengthy CV, rather than a one or two page resume. My thinking here was that it is easier for a hiring manager to read more details in your CV if they are interested than try to infer details from a terse one page …read more
I gave a talk today for the Bloomington Data Collective. You can view the slides or watch the recorded talk. The TL;DR is that profitable strategies are hard to make, but bugs are easy to make, so Bayes' Rule suggests profitable-looking backtests are likely bugs, and here's a catalogue of some of the errors I have seen and committed in my time.read more