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I have prior experience in quantitative finance, analytics consulting, and education technology. Here is my Stack Overflow Careers profile: < http://careers.sta

by p4wnc6 11y ago

I have prior experience in quantitative finance, analytics consulting, and education technology. Here is my Stack Overflow Careers profile: < http://careers.stackoverflow.com/ely http://careers.stackoverflow.com/ely >. My primary experience is in Python, ranging from low-level stuff with llvmlite and writing extension modules in Cython, to database management stuff with SQLAlchemy, through on to tons of stuff with numpy/pandas/etc. I have about 8 years of scientific Python experience if you count grad school, and a little over 4 years of professional work experience. My background is in applied statistics (mostly machine learning for image processing as well as a lot of MCMC methods). I care a lot about software quality and best practices. I also have some experience in one job doing functional programming, and my best functional language is Haskell. I think I'm most motivated by strong attention to quality, so as long as that is a heavy part of the team's ethos, I would be pretty happy working on a wide range of scientific computing / data-focused topical areas of work. But what I find time and again is that people want me to sit in a large open-plan office with undifferentiated desks, where you can't think straight, while cutting every possible quality corner to crank out code for deeply uninteresting parochial business logic. I could happily compromise on some of those things (and every job will have its downsides, which is OK). But I can't find even one job that doesn't require compromising all of those things.

aidenn0 11y ago
Are you currently still in Fort Wayne? I graduated from Purdue 10 years ago, and was interested in staying in the midwest, but my best job offer was a 1 year contract at less than half the wages I took in California as a full-time employee. Fort Wayne is cheaper than Santa Barbara, but not that much cheaper. Furthermore friends who stayed in Indiana describe work conditions very similar to what you mention here. One friend of mine switched from being a developer to a DBA and said everything except being on-call more was a huge improvement: much higher pay, more respect and if he did well it made a difference: his previous two jobs were such that he would get in no way rewarded more (not even someone else noticing) for quality code versus code that implemented only 60% of the features with tons of bugs. Everyone notices if the database goes down.
- p4wnc6 11y ago
  I am in the Fort Wayne area, but more than willing to relocate pretty much anywhere for a good fitting role. Unfortunately, many jobs simply will not provide relocation these days, even if you are willing. I would be happy to work more as a DBA, and already have done some work in that capacity on a consulting project that focused heavily on SQLAlchemy and some database metaprogramming. Unfortunately, my flexibility on the topical nature of my next job has not helped me much. Everywhere I interview still wants to hire people who fundamentally cut corners and de-prioritize quality, all while working for reduced wage and unacceptable benefits. In all of my job searching, the only consistent thing I've seen is that companies want to enforce downward pressure on wages and benefits. It does not seem to matter how much quality degrades or how much market share they need to give up, so long as wages do not grow in any manner proportional to the value that a person's skills or experience can add.
CuriouslyC 11y ago
You have useful skills, you should be quite employable. If you had a track record of conceptualizing and implementing novel tools or solutions to problems based on your ML/statistics background to really tie together the programming and analysis that would be golden. To really gild the lilly, you also would want to have leadership and project coordination experience. The best thing you could do to improve your employability is get together with some other unemployed developers and come up with a really slick tool that leverages ML/statistics and open data to do something cool on the web.
- p4wnc6 11y ago
  It would be very enjoyable to talk further about this. One reason I am hesitant to invest too much time into a prediction-focused side project is that I believe many organizations that purportedly use machine learning actually do not care about prediction, as opposed to marketing or demoware. A major influence on me is a 2011 Cato Unbound article called "Who Cares About Forecast Accuracy" by Robin Hanson [0]. I actually only found the article a few months ago, but it crystallizes the experiences I've lived through for the past 5 years perfectly. Since the social status concerns of executives are typically the primary concerns within any organization, even if a better forecast can add value in some ways, if it risks taking value away in the social status realm, everyone will veto it. As a result, people are often hired purely for credential (this has happened to me before). Then you are asked to do things that are directly damaging to your own career because they take you so far away from your area of expertise or your specialization that they make it harder for you to be hired by anyone else. I have not yet encountered any organization which actually engages in fundamental research about improving forecast accuracy or truly solving problems with A.I. or machine learning. Instead, I've only encountered places that put a thick wrapper of marketing around a thin kernel of simplistic technology, and then spend all their efforts on scaling up the marketing and sales apparatuses around the fundamentally-simple thing. (Simple things are often perfectly fine, of course. But in these situations, the simplicity was not chosen because it was a cost-effective way to meet business needs. Rather, it was chosen because it was cheap and easier to politically control. And after making the choice, no further effort was ever spent investigating whether any type of alternative could improve upon the simple thing in a cost-saving way.) For a long time, I was very bitter about this. But then I realized that if this is the only mode of employment for machine learning researchers and engineers, it might still be OK. If the other aspects of the job afford you ways of meeting other goals, then perhaps it's OK to sacrifice the aspect of intellectual curiosity. Unfortunately for me, the other goals I have include having adequate privacy at work, focusing on software craftsmanship and being proud of things that I make professionally, and maintaining a healthy work/life balance. And it seems these things, like intellectual curiosity, are also mostly impossible to find in modern technology jobs. At any rate, I am not convinced that it would be a wise investment of time to conduct this type of side project. One bad outcome would be for it to embody sort of cargo-cult data journalism practices, like mining for t-stats or something and milking a misrepresentative headline for a bunch of blog hits. An even worse outcome would be to actually solve a problem really well, parlay it into a job offer, and find you have been hired purely as office decoration, to produce demoware or increase value for a potential acqui-hire or whatever. [0] http://www.cato-unbound.org/2011/07/13/robin-hanson/who-cares-about-forecast-accuracy http://www.cato-unbound.org/2011/07/13/robin-hanson/who-care...

by p4wnc6 11y ago

aidenn0 11y ago

Are you currently still in Fort Wayne? I graduated from Purdue 10 years ago, and was interested in staying in the midwest, but my best job offer was a 1 year contract at less than half the wages I took in California as a full-time employee. Fort Wayne is cheaper than Santa Barbara, but not that much cheaper. Furthermore friends who stayed in Indiana describe work conditions very similar to what you mention here. One friend of mine switched from being a developer to a DBA and said everything except being on-call more was a huge improvement: much higher pay, more respect and if he did well it made a difference: his previous two jobs were such that he would get in no way rewarded more (not even someone else noticing) for quality code versus code that implemented only 60% of the features with tons of bugs. Everyone notices if the database goes down.

p4wnc6 11y ago
I am in the Fort Wayne area, but more than willing to relocate pretty much anywhere for a good fitting role. Unfortunately, many jobs simply will not provide relocation these days, even if you are willing. I would be happy to work more as a DBA, and already have done some work in that capacity on a consulting project that focused heavily on SQLAlchemy and some database metaprogramming. Unfortunately, my flexibility on the topical nature of my next job has not helped me much. Everywhere I interview still wants to hire people who fundamentally cut corners and de-prioritize quality, all while working for reduced wage and unacceptable benefits. In all of my job searching, the only consistent thing I've seen is that companies want to enforce downward pressure on wages and benefits. It does not seem to matter how much quality degrades or how much market share they need to give up, so long as wages do not grow in any manner proportional to the value that a person's skills or experience can add.

CuriouslyC 11y ago

You have useful skills, you should be quite employable. If you had a track record of conceptualizing and implementing novel tools or solutions to problems based on your ML/statistics background to really tie together the programming and analysis that would be golden. To really gild the lilly, you also would want to have leadership and project coordination experience. The best thing you could do to improve your employability is get together with some other unemployed developers and come up with a really slick tool that leverages ML/statistics and open data to do something cool on the web.

p4wnc6 11y ago
It would be very enjoyable to talk further about this. One reason I am hesitant to invest too much time into a prediction-focused side project is that I believe many organizations that purportedly use machine learning actually do not care about prediction, as opposed to marketing or demoware. A major influence on me is a 2011 Cato Unbound article called "Who Cares About Forecast Accuracy" by Robin Hanson [0]. I actually only found the article a few months ago, but it crystallizes the experiences I've lived through for the past 5 years perfectly. Since the social status concerns of executives are typically the primary concerns within any organization, even if a better forecast can add value in some ways, if it risks taking value away in the social status realm, everyone will veto it. As a result, people are often hired purely for credential (this has happened to me before). Then you are asked to do things that are directly damaging to your own career because they take you so far away from your area of expertise or your specialization that they make it harder for you to be hired by anyone else. I have not yet encountered any organization which actually engages in fundamental research about improving forecast accuracy or truly solving problems with A.I. or machine learning. Instead, I've only encountered places that put a thick wrapper of marketing around a thin kernel of simplistic technology, and then spend all their efforts on scaling up the marketing and sales apparatuses around the fundamentally-simple thing. (Simple things are often perfectly fine, of course. But in these situations, the simplicity was not chosen because it was a cost-effective way to meet business needs. Rather, it was chosen because it was cheap and easier to politically control. And after making the choice, no further effort was ever spent investigating whether any type of alternative could improve upon the simple thing in a cost-saving way.) For a long time, I was very bitter about this. But then I realized that if this is the only mode of employment for machine learning researchers and engineers, it might still be OK. If the other aspects of the job afford you ways of meeting other goals, then perhaps it's OK to sacrifice the aspect of intellectual curiosity. Unfortunately for me, the other goals I have include having adequate privacy at work, focusing on software craftsmanship and being proud of things that I make professionally, and maintaining a healthy work/life balance. And it seems these things, like intellectual curiosity, are also mostly impossible to find in modern technology jobs. At any rate, I am not convinced that it would be a wise investment of time to conduct this type of side project. One bad outcome would be for it to embody sort of cargo-cult data journalism practices, like mining for t-stats or something and milking a misrepresentative headline for a bunch of blog hits. An even worse outcome would be to actually solve a problem really well, parlay it into a job offer, and find you have been hired purely as office decoration, to produce demoware or increase value for a potential acqui-hire or whatever. [0] http://www.cato-unbound.org/2011/07/13/robin-hanson/who-cares-about-forecast-accuracy http://www.cato-unbound.org/2011/07/13/robin-hanson/who-care...