Other Can biostats be a versatile skill in different industries?

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The discussion centers on the value of obtaining a graduate certificate in biostatistics alongside a pure math master's degree. The individual expresses interest in how skills from biostatistics and epidemiology can be applied beyond the medical field, emphasizing the importance of practical skills in data analysis and programming languages like Python and Julia. There is a cautionary note about the influx of people entering the data science field, raising concerns about the longevity of job opportunities. Participants share insights on how biostatistics skills can translate to various industries, highlighting the importance of mathematical proficiency and data handling capabilities. The conversation also touches on the relevance of advanced computing skills, with examples of biostatisticians successfully transitioning to roles in sectors like finance and oceanography. Overall, the consensus is that while biostatistics is rooted in healthcare, its applications are broad and increasingly valuable in various domains.
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This is sort of half career advice and half academic advice. So I picked one.

So due to some academic hoops I need to jump through it looks like I'll be pretty close to getting a graduate certificate in biostatistics. So, why not? it's a cool cap to my "pure math" masters, develops practical skills, and sounds cool.

I am neither set on nor opposed to a job/career in bio-statistics. My opinion is that learning bio-stats and some epidemiology is a very cool way start doing some applied stats and that those skills can be ported over to any other domain. I'm wondering what people's experiences are with this.

Additionally I am working on my own to learn some programming languages, machine learning, etc. My current job is great about letting me brush up on skills while/between applying them. i.e. if i can use python to do something more efficiently then I'm encouraged to go ahead and do it.

-Dave K
 
Physics news on Phys.org
He's learning DATA SCIENCE! (movie quote I think :=) )

This is great but be aware that many folks are jumping into this field in an attempt to capitalize on the need. I don't know how long this window will be open.

Check out this site for details on numerical computing languages Python and Julia:

https://lectures.quantecon.org/jl/

https://lectures.quantecon.org/py/

This provides links to the Anaconda distribution which gives you all the stuff you need to get started in these languages including the Notebook interface (web page acts like notebook)
 
jedishrfu said:
He's learning DATA SCIENCE! (movie quote I think :=) )

shhhh I managed to go the whole post without actually *SAYING* it.

This is great but be aware that many folks are jumping into this field in an attempt to capitalize on the need. I don't know how long this window will be open.

I think in terms of skills rather than obtaining a particular job title. 5 years from now my title might still be "QA analyst," but like my BFF Matt Damon I think i could (data) science the [stuff] out of my job.

Check out this site for details on numerical computing languages Python and Julia:

https://lectures.quantecon.org/jl/

https://lectures.quantecon.org/py/

This provides links to the Anaconda distribution which gives you all the stuff you need to get started in these languages including the Notebook interface (web page acts like notebook)

Thanks.

-Dave K
 
I don't pretend to know much about them but there are plenty of applications of algebraic topology to data science. Maybe look into persistent homology/topological data science if you haven't already.
 
Infrared said:
I don't pretend to know much about them but there are plenty of applications of algebraic topology to data science. Maybe look into persistent homology/topological data science if you haven't already.

I've studied it a bit, but it hasn't really made it's way out of academia into "marketable skill" yet except for a very few companies - the kind that exist in NYC and California and hire PhDs. If it does start to come around into more popular usage I will certainly have an edge there over the pure stats people, I should think.

But my question is more basic. I'm wondering how Bio statistics/Epidemiology people have possibly found that their skills have ported well outside the medical sciences.

-Dave K
 
I should think their skills ported well as those companies which hired them are primarily interested in the math portion of their skillset. The analysis data comes mostly from internet logs and so you just need to know how to extract, transform and load it into a database for analysis and then its the analysis that's key.
 
jedishrfu said:
I should think their skills ported well as those companies which hired them are primarily interested in the math portion of their skillset. The analysis data comes mostly from internet logs and so you just need to know how to extract, transform and load it into a database for analysis and then its the analysis that's key.

That's what I would thing as well. I took a biostats course and I didn't find my lack of biology training to be harmful in any way.
 
I think a job in biostats probably requires a Masters. I think that's what you're getting? I work in the biostats dept at a medical school and everyone has a MS or PhD. I'm not sure how other depts do it though, as here we have it split between biostatistics and bioinformatics, with bioinformatics requiring more computing skills (and lesser stats skills, in my case).

A lot of the topics in biostats are general, so I think it should be applicable to else where. Even more so if it polishing your skills in R or Python. I personally haven't met an biostatisticians outside of the healthcare though. I've seen a lot of PhDs in oceanography where I live working as data scientists in local banks since the local PhD program provides good training in R. So I think you'll be good as long as you get the computing part down.
 
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