It has been a couple of months since my last update and this post will essentially bring to conclusion the “diary” of my data science self-education endeavor.
For a number of reasons (professional and personal), I moved on from my prior place of employment for the past 19 years. It was a successful ride and I certainly hope I gave as much as I had received in my time there. During my final year there as CIO, I had become enamored with the field of Data Science and began documenting my exploration in this field. My last day with them was April 1 and I took advantage of newly found free time to spend more time with studies as well as relocating from New York to South Carolina.
My plan was to find employment in SC in the realm of Data Science (or at least something in the Data Analytics field that could transition to Data Science). I took a little sabbatical over the summer and began my search in earnest after Labor Day. I created a resume (I’ve not had to use one in nearly 19 years) which I believe highlighted my education (undergraduate degree in Math & Physics, graduate degree in Physics), my real-world business experience in the Supply Chain industry and my Data Science certifications (as thoroughly documented in this blog).
As with most elements in my life, things did not go according to plan (just ask my two ex-wives!). Here are some of the challenges I encountered.
- South Carolina is not a hotbed of Data Science activity. Job board searches in South Carolina for “Data Scientist” generate less than a handful of hits. Travel north to North Carolina or west to Atlanta, and you’ll find a land of opportunity. There were a handful of openings in Charleston and Columbia, but sadly, those cities are hours away from where I live.
- You need to live in/near a big city. When I attended ODSC East in Boston back in May, I observed at the Career fair that recruitment for new Data Scientists was primarily near large cities. If you have the passion for DS and the flexibility to move, head to Washington DC, NYC, Boston, Chicago, Seattle, San Francisco, etc. Unless you’ve a well-established track record in the field, telecommuting is not likely to be an option. For me, it was too much to ask my wife to leave her career of 20 years to uproot the family, leave the town of her birth, her friends & relatives and gamble with me on a new part of the country.
- My career history may have been too intimidating for employers looking to fill lower-level positions. When I realized that pure data scientist positions were not to be found near me, I began to seek any role in a data analytics related field. I knew realistically that what I was seeking would have resulted in a salary that was half or even less than what I had been making before. Fortunately, I was in a position where the salary wasn’t as important to me as the challenge of entering a field where I’d be intellectually challenged every day. And I was confident that as I gained experience, my salary would commensurately improve. However, despite explaining my situation & desires in a cover letter, it might have been too much for a potential employer to see a resume of a former CIO applying for a position that may have been far down on the organizational chart. While climbing the ladder is acceptable, stepping down & starting over causes some consternation.
- Lack of experience and education in Data Science. For all the courses I completed, books I’ve read, and certificates I’ve received, it still doesn’t add up to a PhD, let alone a Masters Degree in Data Science. I had hoped that my real-world experience would’ve compensated for this, but it turned out not to be the case. Unfortunately, Masters Degrees are not cheap (I know, I already have a couple) but as I’m already funding two of my children through college, I just didn’t have it in me to fund a third (me). I’m convinced that the education I’ve received is equivalent to any MS program in the subject, but I can certainly see from an employer’s point of view that a formal education is more of a guarantee of the skillset being advertised on the resume.
If I had to do it over, I would’ve gotten involved in publishing data projects much earlier on. In my view, I had wanted to make sure I had attempted to learn about as many techniques as possible before tackling publicly available datasets. Instead, I should have been tackling them and publishing my work (i.e. on Github) back when all I knew was linear regression. I didn’t have an extensive library of original work and by the time I felt comfortable doing so it was really too late to make a difference in my employment search. I hadn’t built up a network of collaborators and peers in the subject area and striking out on my own proved to be fruitless.
A Happy Postscript
One thing that I’ve learned in my 40+ years of existence is this: Just because you didn’t end up where you planned, it doesn’t mean you’re not where you’re meant to be.
I am actually thrilled to announce that I’ve begun the next phase of my career with a fantastic company. As of last week, I have been hired into the role of Product Manager with NCR. I’ll be in charge of setting the vision, strategy and execution of their ERP product for the Distribution & Wholesale space. I remain in the same Supply Chain industry that I’ve spent the past two decades in, and as my new boss tells it, I get to join the “dark side” of being a technology solutions provider instead of being the consumer.
It’s a great opportunity that came to me unlooked for and is filled with potential to work with some great technology minds worldwide to create solutions to real-world problems.
Have I completely abandoned Data Science? Heck no. I believe that one of the reasons NCR hired me was my knowledge of the subject. I personally plan to introduce the practice of pattern recognition, predictive analytics and decision making into the software platform that I’m now responsible for. Although I will not be able to spend 8 hours a day playing in R, Python and Spark, I will be keeping tabs reading other blogs and books, and maybe tinkering around in R from time to time. But first, I still need to figure out where the bathrooms are in this massive organization.
I’m glad to have heard from many of you who found my personal journal to be of help. I wish all of you well on your journey – regardless of where it takes you!
– Bill Kimler, 12/31/2016
dreaming of data 