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Ask DT: Interested in sustainability and data science
3 points by nick-transition 3538 days ago | 2 comments
Hi everyone! I am a recent Bioengineering graduate interested in using data to help better inform corporate decision-makers. I have worked in sustainability research but there was not enough problem solving to keep me interested. Now I am trying to figure out how to turn a passion for sustainability and an interest in data science into a career path. My computer programming experience is middle of the road but I have had success using python to solve data manipulation issues (hacker style). I am interested in either pursuing (Option 1) a Master's in Data Science or (Option 2) developing this skill set while working in corporate sustainability.

Regarding Option 1, federal funding is available to reduce the out of pocket cost of education (which is a VERY big deal), but I have a few questions. NSF Funding Example: http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141 -How competitive is this type of funding? (I have seen some statistics, but I would love to hear a first hand account)

Option 2 would be more ideal, but I am not aware of any organizations looking to hire "apprentice" data scientists with complimentary skills. -Has anyone been able to negotiate for such a position? -Any thoughts on how to reach out to organizations about something like this?

Thanks for the insights and let me know if you have any thoughts.



2 points by eddotman 3538 days ago | link

I'm in a somewhat similar situation to you: I graduated with a Bachelors in Science and I have some programming experience.

I suspect I'm too early on my path to offer you any real advice, but I can tell you where I'm headed and maybe that will be helpful in some way.

More or less, I'm pretty much taking your "Option 1" with a twist. I'm starting a PhD program soon, which has the disadvantage of taking more time, but the advantage of having no (direct) cost. It's fully funded with a salary provided, as per usual for STEM PhD programs.

The research I'm doing is related to materials processing and predictive modelling of processing routes (using some mixture of ML, NLP, etc.).

Anyway, I think the main useful takeaway is that you can avoid the out of pocket cost if you look at PhD programs rather than masters programs. In principle, you can always leave a PhD program with a masters (though it's somewhat dishonest to apply with this intent).

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1 point by demian 3535 days ago | link

If I were you I would take a hybrid route, focus on improving my programming skills to create a portfolio of projects using open data WHILE working on a graduate degree with an advanced mix of statistics and computer science.

Personally I wouldn't take a "Data Science" course, it's still "to novel" to tackle it as a full blown degree in academia. Instead I would focus on something related to the field you are interested in, while taking advantage of your backgroud. Something like a masters in bioinformatics/biostatistics focusing on sustainability issues.

ps: with the hybrid route you can graduate with (a) a portfolio proving hands-on experience and (b) academic credentials in your chosen application field.

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