I have prior experience in quantitative finance, analytics consulting, and education technology. Here is my Stack Overflow Careers profile: &lt; <a href="http:&#x2F;&#x2F;careers.stackoverflow.com&#x2F;ely" rel="nofollow">http:&#x2F;&#x2F;careers.stackoverflow.com&#x2F;ely</a> &gt;.<p>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&#x2F;pandas&#x2F;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.<p>My background is in applied statistics (mostly machine learning for image processing as well as a lot of MCMC methods).<p>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.<p>I think I&#x27;m most motivated by strong attention to quality, so as long as that is a heavy part of the team&#x27;s ethos, I would be pretty happy working on a wide range of scientific computing &#x2F; data-focused topical areas of work.<p>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&#x27;t think straight, while cutting every possible quality corner to crank out code for deeply uninteresting parochial business logic. I could happily compromise on <i>some</i> of those things (and every job will have its downsides, which is OK). But I can&#x27;t find even one job that doesn&#x27;t require compromising <i>all</i> of those things.