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Comment by gfodor | Hacker News Reader

Great post -- I want to throw out another option though, which I am exploring myself. Your post seems to, like most posts on HN, be a very "web application" centric view of things.

There are obviously vast worlds of software engineering outside of web applications. Embedded/real-time systems, programming languages & tools, robotics, graphics, bioinformatics/computational biology, machine learning, machine vision, the list goes on. Why not "pivot" your career into a completely new subfield? The downsides: you will likely need to take a year off for self study and to build up a body of work to land you a job, and you will have to take a pay cut. But you will be able to build stuff, will remain excited on the edge of your field, and might be able to have a fresh slate and replicate those feelings you had when you started off in the first place.

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Richard Hammings has a similar advice regarding scientific research: "Somewhere around every seven years make a significant, if not complete, shift in your field. Thus, I shifted from numerical analysis, to hardware, to software, and so on, periodically, because you tend to use up your ideas. When you go to a new field, you have to start over as a baby. You are no longer the big mukity muk and you can start back there and you can start planting those acorns which will become the giant oaks."

http://www.paulgraham.com/hamming.html

Hamming is great. I try to re-read his "The Art of Doing Science and Engineering" once every year or so.

Sounds like what I want to be doing. I'm curious if you have additional insight on taking on this path, I want to keep all of my options open and instead of say just pursue embedded/real-time systems and find out that the field is too narrow. What do you recommend to study as opposed to CRUD web-apps,

C/C++, ML, data analysis with Python/R or learn more domain specific knowledge such as Bioinformatics or graphics or quant finance? Much appreciated, thanks.

I'm not clear if you're saying you do or don't want to be in embedded, if you do then try hanging out in:

  comp.arch.embedded

for a few weeks, find mags related to embedded.

It depends a lot. This is opinion, but I would say that there are three big categories of software development skills. Of course most jobs are a mixture of these.

1. Web development (transport-level and higher networking, HTML/JS/CSS, PHP/Perl/Python/Ruby, using databases, etc.)

2. Enterprise software design (domain modeling, OO programming, system architecture, scaling, security)

3. High performance (algorithms, advanced data structures, C/C++, memory management, DB internals, internet-layer and below networking, cryptography)

It sounds like you want to get into 3. A good way to start is algos/data structures. Almost all the fields the parent listed benefit from a very strong foundation in computer science: discrete math, linear algebra, algorithms, advanced data structures, etc.

Data analysis with python/R is more for scientists and mathematicians, not software developers. If you are being paid to analyze data as a programmer, usually you are analyzing very large data sets and you will be using a much more performant language or possibly even a highly parallelizable paradigm like MapReduce.

The easiest path into a nr 3 job here is to find a job with an engineering product company, ie a company that sells a high-tech product that is not software.

My current job mixes those three categories nicely and I love it :)

I am a database developer in a sequencing center. I would not recommend bioinformatics if you have any passion for good quality code.

There are some decent bioinformaticians out there, but most of them write crap 100 line scripts, and have very little desire to learn more than the basics. I am getting increasingly frustrated, as I can see I am clearly writing significantly smarter software then these people (most of them are just counting things and plotting the counts on a graph). I am seen by management as being the same kind of skill level / skill set.

If of course you are really interested in the research, then you may like it, but do not expect your coding skills to be valued.

hi collyw, thanks for your message. I'm indeed really interested in Bioinformatics. I've had experiences in undergrad similar to what you described (e.g., a folder with 50 Perl scripts that does a variation of the same thing).

I don't really mind the management slights as it's an occupational hazard of a programmer. What bothered me about academic research was how the doors were shut for you if you did not pursue the traditional PhD/post-doc path of life sciences research. Also that pure Bioinformaticians even with academic pedigree was considered lower in the pecking order in comparison to "wet-lab" folks.

As crazy as it sounds, I really miss the days of writing Perl scripts (Python probably now); running BLAST and plotting Information Theory graphs. How do you like your current gig and what do you recommend for someone who is looking to jump back into it?

My current gig has ups and downs. I like getting to code things from scratch in the technology of my choice, but too often we are using the quickest crappiest solution to get things done (uploading database data using excel - supposed to be a temporary solution, but has been going on for two and a half years).

Apparently most labs have a shortage of bioinformaticians (at least that's what I hear here in Europe).

Yes, having a PhD will be helpful if you are looking towards a more research oriented side of things. If not you are more likely to be more of a technician, and your work will be a bit more production like.

My advice would just be to look at institutes that you would be interested in working at - their job pages. I am sure you could start with more production style things and move into a more research oriented role.

Here is the jobs page for science park I work in in Barcelona (pay doesn't sound much compared to the US). Not much up there just now, but I know we are hiring more people soon.

http://www.pcb.ub.edu/homePCB/live/en/p2466.asp

>> The downsides: you will likely need to take a year off for self study and to build up a body of work to land you a job

I am doing this myself. It's a risk but I think the rewards are worth it!

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