Gone are the days when employers would hire someone just for having a PhD. Those are a dime a dozen now and it's only natural to pick those who come equipped with the right skills. In the coming months, I will be teaching myself:
- Python
- SAS
- R
Python is a general purpose language that is easy to learn and versatile because of its object-oriented nature and huge user support base. I have already written some small, simple pieces of code. As a more substantial exercise, I will convert a series of my existing Matlab codes for solving differential equations to Python.
SAS and R are popular statistical programming tools, meant to enable quick implementation of standard models and algorithms. My experience with them has so far been limited to course work. To get myself better acquainted with SAS and R, I will sign up for Kaggle competitions. Before that, I am going to need a refresher in machine learning theory.
Technical skills aside, it would likely be useful to know how data science impacts the businesses that utilize it. Here, I shall consult business books on the topic. I have identified a few at the local bookstore, and they look like they would make for nice bedtime reading.
Wednesday, March 4, 2015
The Startup Lure
Attended a small presentation at 1871 last night, about how Chicago's startup scene is flourishing and how one might participate. It really is quite astonishing how investments flowing into startups have been growing so quickly over the years. There are now a good number of startup accelerators or incubators based in Chicago, to which founders apply to receive a small startup grant, space to work in, and very importantly, mentorship help. Needless to say, admittance to these programs is extremely competitive.
Even for those who are not founders, there are benefits to working for a startup, namely the opportunities to learn a lot (and this could not be stressed enough), the street cred working in a startup gives you, and the opportunity to hold a significant amount of equity in the company. The downsides are also pretty scary, and mainly has to do with the fact that 90% of startups fail. Since you would be paid mostly in equity, there is a good chance you will end up with nothing to show for all your efforts. Though perhaps the knowledge gained and the resume boost would make up for that.
Anyway, a few great resources for startups and potential startup employees are
Startup statistics trackers: BuiltInChicago, CrunchBase, and AngelList,
Startup accelerators: Startup Institute, TechStars, Good Food, Health2.0 (there are a lot more out there, and they tend to be very specific),
Startup networking events: Startup Weekends, Uncubed, BuiltIn Brews.
The budding data scientist might consider springboarding his/her career from a startup.
Even for those who are not founders, there are benefits to working for a startup, namely the opportunities to learn a lot (and this could not be stressed enough), the street cred working in a startup gives you, and the opportunity to hold a significant amount of equity in the company. The downsides are also pretty scary, and mainly has to do with the fact that 90% of startups fail. Since you would be paid mostly in equity, there is a good chance you will end up with nothing to show for all your efforts. Though perhaps the knowledge gained and the resume boost would make up for that.
Anyway, a few great resources for startups and potential startup employees are
Startup statistics trackers: BuiltInChicago, CrunchBase, and AngelList,
Startup accelerators: Startup Institute, TechStars, Good Food, Health2.0 (there are a lot more out there, and they tend to be very specific),
Startup networking events: Startup Weekends, Uncubed, BuiltIn Brews.
The budding data scientist might consider springboarding his/her career from a startup.
Friday, February 27, 2015
Initialization
In this first post, I briefly describe myself and the reason I made this blog. I am in the final year of my PhD program, with a couple of projects left to finish up before I write my dissertation. Like many of my ilk, I pursued this path for the love of physics and with the expectation of carving out a career in academia.
Over the course of my academic career, I've picked up a good number of skills for my work, in programming and in analysis techniques. These skills, as I was told by an alum who returned to talk about his work in the finance industry, are sought after outside the ivory tower. And so I've been wondering for awhile, if I would be better off outside the protective walls of academia, applying my training to real-world problems, studying how the vast machinery of society, of the economy, operates.
Better pay aside, I am drawn also by a certain excitement about experiencing a completely different environment, working within new social and organizational frameworks. Or maybe it is foolhardiness, like the average American tourist going to live with a New Guinean headshrinker tribe. Within the academic community, there exists a special disdain for those who "sell out". By "special", I don't mean "strong"; it is, in fact, rather subtle, and fades by the day, as conditions for working in academia deteriorate (Google "academic job market" for specifics). But I digress.
Ultimately, what brought me to my decision to leave academia after graduation was a lifelong desire to explore as much of human phase space (the human experience, the world, what have you) as I can. I execute this plan not without trepidation - there is much to learn and many mistakes to make - and so I will blog about my experiences here both as a means of self-reflection and as a reference for myself in the future.
Over the course of my academic career, I've picked up a good number of skills for my work, in programming and in analysis techniques. These skills, as I was told by an alum who returned to talk about his work in the finance industry, are sought after outside the ivory tower. And so I've been wondering for awhile, if I would be better off outside the protective walls of academia, applying my training to real-world problems, studying how the vast machinery of society, of the economy, operates.
Better pay aside, I am drawn also by a certain excitement about experiencing a completely different environment, working within new social and organizational frameworks. Or maybe it is foolhardiness, like the average American tourist going to live with a New Guinean headshrinker tribe. Within the academic community, there exists a special disdain for those who "sell out". By "special", I don't mean "strong"; it is, in fact, rather subtle, and fades by the day, as conditions for working in academia deteriorate (Google "academic job market" for specifics). But I digress.
Ultimately, what brought me to my decision to leave academia after graduation was a lifelong desire to explore as much of human phase space (the human experience, the world, what have you) as I can. I execute this plan not without trepidation - there is much to learn and many mistakes to make - and so I will blog about my experiences here both as a means of self-reflection and as a reference for myself in the future.
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