BookmarkSubscribeRSS Feed
jenjsmall
Calcite | Level 5

Hi there,

 

This is kind of off-topic for this group, but hopefully some people can give me some advice. I've worked about 10 years in epidemiological research as a SAS programmer/analyst, but never clinical trials. I'm interviewing at a pharmaceutical company tomorrow for a statistical programmer position (seems like it's their entry level programming position) and I know they'll ask me technical questions. 

Do you have any suggestions on what I should brush up on before the interview? 

 

What kind of programming is involved? Is it all macros? 

Are there any standard macro statements/functions/variables I should definitely know?

Should I study up on SAS character and numeric functions? Any in particular that are used often? 

Does everyone use SQL these days or can I do things in a data step?

 

I've googled a lot of clinical trial SAS programs and the macros look so unbelievably advanced. I'm afraid I might have psyched myself out for the interview tomorrow! 

Thanks for any advice, I'd really love to transition to clinical trials and get some new skills!

Jen 

1 REPLY 1
FreelanceReinh
Jade | Level 19

Hi @jenjsmall and welcome to the SAS Support Communities!

 

I transitioned to clinical trials in 2005/2006 and went through interviews at about 10 pharmaceutical companies and CROs between 2005 and 2010 (only in Germany and Switzerland, though).

 

Even if interviews in your country (U.S. or Canada, I assume) were very different from those in D/CH, I'd say: Don't worry about the technical questions now. With 10 years of SAS experience you should have seen and used so many techniques and methods that you know how to tackle interview-type problems or what to say about SAS programs that might be shown to you. 


@jenjsmall wrote:

What kind of programming is involved? Is it all macros? 


Not in my experience. Most companies have their own standard macros for repetitive tasks such as adverse event reporting. These macros are indeed very complex, but you would normally deal only with macro calls, not with the macro code behind the scenes. As they are company-specific, nobody will ask you interview questions about them. Of course, familiarity with the basics of macro programming will be expected from anyone with several years of SAS experience.

 

The preparation of analysis datasets involves all sorts of data transformation techniques. PROC SQL is very common and useful for this, but wasn't one of my strengths when I transitioned to the pharma business. What statistical procedures are most frequently used (for efficacy analyses, as opposed to safety) depends on the therapeutic area. Obviously, survival analysis (in the broader sense of time-to-event analysis) plays an important role in clinical research, besides (generalized) linear models, etc. Typically, the majority of SAS programs will produce summary tables, listings and (to a lesser extent) graphs -- or validate outputs of these kinds. PROC REPORT is frequently used for (production) tables and listings that are not covered by standard macros.


Should I study up on SAS character and numeric functions? Any in particular that are used often? 

I don't think so, assuming that you already know plenty of these.


Does everyone use SQL these days or can I do things in a data step?

Many things can be done in a data step and with other procedures, but completely excluding PROC SQL would be too strong a limitation.

 

One area that has become increasingly important over the last decade is CDISC. So, you should have heard about the role of SDTM and ADaM standards in today's business practice.

 

Good luck with your interview and your transition in general!

sas-innovate-wordmark-2025-midnight.png

Register Today!

Join us for SAS Innovate 2025, our biggest and most exciting global event of the year, in Orlando, FL, from May 6-9. Sign up by March 14 for just $795.


Register now!

Mastering the WHERE Clause in PROC SQL

SAS' Charu Shankar shares her PROC SQL expertise by showing you how to master the WHERE clause using real winter weather data.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 706 views
  • 1 like
  • 2 in conversation