staying with R, jobs in R

-----Original Message-----
From: Weiwei Shi [mailto:helprhelp at gmail.com] 
Sent: Monday, August 29, 2005 9:05 AM
To: Berton Gunter
Cc: roger bos; avneet singh; r-help at stat.math.ethz.ch
Subject: Re: [R] staying with R, jobs in R

Hi, there:
Could I ask another question, which is a little bit off-topic; but I
tried hard and did not get good enough info... so please help

I am very interested in seeing where to find those
bio/pharmaceutical-related industries, using R and data mining as
approaches?

thank you very much!

weiwei

On 8/29/05, Berton Gunter <gunter.berton at gene.com> wrote:

Avneet:
Not to throw a wet blanket on your enthusiam for R (which I 

share) but ...

-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA

"The business of the statistician is to catalyze the 

scientific learning

process."  - George E. P. Box


 Your better off finding a

job you like
at a company you like and then convincing them that R is
better (not to
mention the R skill set you are bringing to the table).
 Good luck to you.
Roger

Fine advice, but a tad unrealistic. The reality (according to Bert):

1. Most jobs for statisticians are in the 

pharmaceutical/medical industry

(which includes academic research centers) in clinical 

trials. Data: See job

ads in Amstat News.

2. For better or worse, in this arena SAS is the standard. 

You will **not**

-- repeat, NOT -- convince industrial employers who have 

thousands of lines

of legacy infrastructure code and legions of SAS 

programmers to change. You

may well make some inroads in academic research venues. In 

both, you will

generally be free to use whatever software you like for 

your own work, but

the final code submitted for FDA approval will almost 

certainly necessarily

be SAS. Rail all you like, but those are the realities.

3. Another significant amployer of statisticians these days 

is the "finance"

industry (credit scoring and the like). Data: See Amstat 

News ads again.

There S-Plus is already widely used, so you should have no 

difficulty using

R and even getting others to adopt it.

I think outside these arenas -- for example, in industrial 

research and

engineering centers or in pre/non-clinical pharmaceutical 

work, you'll again

be free to use what you like. But there are relatively few 

jobs there, so

that despite Roger's noble advice (with which I again 

agree), first you

gotta eat and pay the mortgage.

And I also say: good luck.

-- Bert

-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA

"The business of the statistician is to catalyze the 

scientific learning

process."  - George E. P. Box