Restart

Beginning Again

My last post to this blog was in October of 2016. I began posting to this blog nearly five years ago from the depths of my doctoral program. The observation I had made at the time, however, is as true then as it is today: in order to stand out from the crowd in data science, it is imperative that one maintains multiple extra-curricular projects on top of whatever is happening during one's day job. Many of the data scientists I follow on social media appear to be experts at juggling their actual work load as well as contributing to open-source projects, performing science communication through social media and blog posts, and hacking on side projects. I am picking up this blog to achieve similar: sharpen my rapidly oxidizing writing skills, write about topics that interest me, document data science projects I work on on the side, and of course pad my portfolio. 

Post-Grad

I have more or less successfully made the transition I had hoped for out of my doctoral program and into the private sector over the course of the last two years. I was privileged enough to be offered a part-time contracting gig before I had received my doctorate at an environmental consulting firm that provided the perfect segue out of public or private conservation biology work into a more purely business-oriented data science position. While I truly miss the deep personal connection I felt with conservation biology work, I am in a much better job track and industry for my overall emotional and financial health (not to mention career opportunity and stability). Of course there was a massive learning curve associated with my jump into business analytics, but I have taken refuge in the fact that the mathematical tools and statistics are the same, and I can learn the new context on the fly. My current job also required a dive into the deep end in SQL and Oracle database structure, an experience that has been at times painful but which I am now very thankful for. Working closely with our DBA, I have learned an incredible amount about not only retrieving the data I need in a useful format, but also internal database construction and operations and database and query performance tuning.

Why Blogging?

I mentioned at the start that I had made the observation several years ago that it appeared that successful data scientists maintained a diverse extra-curricular portfolio on top of whatever they were doing from 9-5. From the comfort of full-time employment, I can appreciate why this is necessary in this field. For the last two years, I have completed several projects wherein I've learned new R packages, learned Python and SQL basically from scratch, developed new analytical products and metrics, and so on; none of what I have done for my current employer can be shared because it is all proprietary to the employer. The world of proprietary business knowledge was not something I thought of much in my past life as a biologist, to be honest. However, a company seeking to pay a mid- to senior-level data scientist the market rate would certainly be within their rights to seek some evidence that applicants can do what they say they can do. I have also grown to appreciate the differences that exist between understanding in theory how some particular package or model works, and successfully implementing that package or model. Since all of my 9-5 work is proprietary, how would I be able to prove that I know what I'm talking about, or have done what I say I've done. Enter the extra-curriculars.