The Surprising New Face of Today’s Gatekeepers: Race and Gender in Pharmaceutical Medical Information Interviews


Originally published/last updated on myearlyretirementjourney.com on Dec 20, 2019. 

Admittedly interviews engender feelings of a deer-in-headlights for the single girl. I prepare as much as I can scouring the internet for interview questions; recording and reviewing past interview questions I have received; prepping with colleagues and old mentors. I haven’t found the golden ticket. Or I’m destined for life in the call center.

I may go in to these interviews confident, but once I enter the interview room, the discomfort of those around me is electric and palpable.  I always feel put on the spot and because I don’t look like them I second guess their questions and my answers. Are they trying to trick me? Why are they asking me this? Do they ask other people these questions? Is “articulate” a skill they mention they’re looking for to other candidates at this level?
I generally feel as though I’m coming in at a deficit. Did you really go to these schools? I’ve been called untrustworthy of the process, but not because I was born this way. I was programmed this way. People like people that are like them. That’s not something that most people contest. It’s something I’ve had to manage once I left the comfort of my small rural town in Illinois. But most people in roles of influence may not have had to do so.  Their discomfort spills into the interview sessions, and it changes the energy of the experience for those involved. That has been my experience.
Basically what instigated this post was the feeling that everyone I was interviewing with was an Indian woman.  When I LinkedIn them, other people in those roles at other companies seemed to confirm my suspicion. I’ve only now learned how to completely defer to a white man in these types of situations. Imagine my surprise when nary a white man was in sight. Now there’s a whole new culture of people I have to learn to bow down to? Yes, I’m aware of how that sounds. But most Americans are used to seeing white men in high-ranking roles, calling the shots, and getting away with whatever. #metoo #timeisup I.am.used.to.that.
So I thought I’d compile some data to support my narrative. I thought I was going to present some shocking results about how 99% of all hiring managers in biopharmaceutical medical information roles were Indian women. It really felt that way, irrespective of my former and current Indian-women-managers. But it turns out maybe I’m a little bit of a racist white man. You see one or two people that don’t look like you (read: a white man), and you feel as though your position in society has been taken over by “the colored people.” The data didn’t exactly match the narrative I had in my mind, but it was pretty darn close.

Race and Gender Demographics in Pharmaceutical Medical Information Roles

CompanyPositionHRHR RaceHR GenderInterview PanelInterview Panel RaceInterview Panel Gender
Pacira (NJ)Sr Manager, Medical InformationBFblack x 1female x 1n/a
ADMA Biologics (Tampa, FL)Medical Information SpecialistWFwhite x 1female x 1WF
AF
white x 1
Asian x 1
female x 2
G1 Therapeutics (Durham, NC)Medical Affairs Operations ManagerWFwhite x 1female x 1WM x 2
WF x 1
IF x 1
white x 3
Indian x 1
male x 2
female x 2
Avexis (Bannockburn, IL)Sr Manager, Medical InformationAFAsian x 1female x 1WFx2, IFx3,  AF x 2, WMwhite x 3
Indian x 3
Asian x 2
male x 1
female x 7
UCB (Atlanta, GA)Medical Communications LeadBFblack x 1female x 1n/a
RakutenSr Manager, Medical InformationHMHispanic x 1male x 1WMwhite x 1male x 1
IQVIA (Durham, NC)Operations Specialist 2IMIndian x 1male x 1WM, IFwhite x 1
Indian x 1
male x 1
female x 1
NovoNordisk (NJ)Medical Information ManagerWF, BFwhite x 1
black x 1
female x 2WF x 1
IF x 2
white x 1
Indian x 2
female x 3
KedrionMedical Information ManagerHFhispanic x 1female x 1n/a
Pharmacyclics (CA)Sr Mgr – Scientific Communications Medical ReviewWFwhite x 1female x 1AFasian x 1female x 1
Raleypta (CA)Mgr, Med InfoWMwhite x 1male x 1n/a
Greenwich Biosciences (Carlsbad, CA)Sr Med Info ScientistWFwhite x 1female x 1
Takeda (Cambridge, MA)Mgr, Med InfoWF
AF
BF
white x 1
Asian x 1
black x 1
female x 3WF x 2
ROWF x1*
IM x 1
white x 2
ROW x 1
Indian x 1
male x 1
female x 3
AstraZeneca (MD)Sr Mgr Med InfoBFblack x 1female x 1n/a
Myriad Genetics (Mason OH)Medical Information Liaisonn/aWFwhite x 1female x 1
Novartis (NJ)Real Time Medical Information ManagerWF
IF
white x 1
Indian x 1
female x 2WF x 2
IF x 2
AM x 1
white x 2
Indian x 2
Asian x 1
male x 1
female x 4
Dermira (Menlo Park CA)Senior Manager Medical InformationHM
WF
white x 1
Hispanic x 1
male x 1
female x 1
WFwhite x 1female x 1
Table Legend: M = male, F= female, W = white, B = black, I = Indian, A = Asian, ROW = Rest of World (common term in pharma)
From June 23, 2019 to Sept 25, 2019, I applied to roughly 116 jobs nationwide in primarily medical information manager roles at biopharmaceutical companies of varying size. Of those, I got callbacks on  17. That’s a 14.6% response rate.  The data shown here is based on the seventeen callbacks.
From the seventeen callbacks, I encountered 21 HR personnel. Of those, 17 (81%) were female and 4 (19%) were male.
In tabulated form, the data is as follows.
HR Personnel
Male19%
Female81%
Of those, race was broken down as shown in the following table.
HR Personnel
White42.86%
Black23.81%
Asian19.04%
Hispanic14.29%
If I moved past (or skipped altogether) the HR initial screen to a hiring manager or onsite interview, I encountered a total of 32 interviewers.  Of the 32 interviewers, 25 were female (78%), and 7 (22%) were male.
Interview Panel
Male22%
Female78%
Of the 32 total interviewers, 16 (50%) were white; 10 (31%) were Indian, 5 (16%) were other Asian (non-Indian), 1 (3%) was from Rest of World (ROW).  In the US, for census demographics, Southeast Asian (e.g. Indian) and Asian are generally lumped together as Asian, so of the 32 interviewers, 15 (47%) were Asian.
The ROW interviewer was a Brazilian female who lived and worked in Brazil. If she resided in the US permanently, I would have included her as a Hispanic female as she would be classified as a minority and treated as such. But as she has the luxury of living in her home country and enjoying the benefits of being part of the majority, for the purpose of this analysis, I counted her as ROW or Other.
In tabulated form, the data is as follows.
Interview Panel
White50.00%
Black0.00%
Asian47.00%
Hispanic0.00%
Other3%
So yes, my wildly race-centric brain coded my interviewers as primarily Indian women not because that was actually true but largely due to the over-representation of Indians in the interview process.
What does over-representation mean, you ask?
Simple. When you look at the population demographics as a whole, one would expect (or hope for) those same demographics in just about every societal situation where race shouldn’t matter ranging from academics, hiring, leadership, welfare, crime stats, etc.  When one group appears more or less in a subsect of society, in this case med info in pharma, that group is considered over- or under- represented, respectively.
In tabulated form, here are the latest population demographics estimated from the US Census Bureau, as of July 1, 2018.
Percentage
Male
Female50.80%
I suppose we are to conclude that the male percentage is everyone not tabulated as female. Shockingly, women are now the (slim) majority! (Yes, single girl, you will die alone.)
Percentage
White alone76.50%
Black alone13.40%
Asian alone5.90%
Hispanic18.30%
White alone, not Hispanic60.40%
Side note. I’m always struck by the order of the races in these tables. It’s not alphabetical; it’s not numerical…
Now let’s compare this US Census data to what we saw with our HR personnel and Interview Panels. Note my classfication of Hispanic was based on my identification, but outside of name origin, accent, and skin color, I had no way of knowing if a White Person classified themselves as of Hispanic origin. Thus, I included both ‘White alone’ and ‘White alone, not Hispanic’ in my tables for comparison. But my tabulated entry for “White” stayed the same.
Gender – HR Personnel
US PopulationHR PersonnelRepresentation
Male19%UNDER
Female50.80%81%OVER
Gender – Interview Panel
US PopulationInterview PanelRepresentation
Male22%UNDER
Female50.80%78%OVER
Race – HR Personnel
US PopulationHR PersonnelRepresentation
White alone76.50%42.86%UNDER
Black alone13.40%23.81%OVER
Asian alone5.90%19.04%OVER
Hispanic18.30%14.29%UNDER
White alone, not Hispanic60.40%42.86%UNDER
 Race – Interview Panel
US PopulationInterview PanelRepresentation
White alone76.50%50.00%UNDER
Black alone13.40%0.00%UNDER
Asian alone5.90%47.00%OVER
Hispanic18.30%0.00%UNDER
White alone, not Hispanic60.40%50.00%UNDER
For funsies, let’s look at the hiring process as a whole (HR + Interviewers).
Gender – Total Hiring Process
US PopulationTotal Hiring ProcessRepresentation
Male21%UNDER
Female50.80%79%OVER
Race – Total Hiring Process
US PopulationTotal Hiring ProcessRepresentation
White alone76.50%47.17%UNDER
Black alone13.40%20.00%OVER
Asian alone5.90%35.85%OVER
Hispanic18.30%5.66%UNDER
White alone, not Hispanic60.40%47.17%UNDER
In summary, for medical information manager roles in the pharmaceutical industry, white males are largely under represented in the hiring process. Shocker!! By an overwhelming majority (79%), women are over represented in the decision making that goes into hiring medical information managers at the level of HR and Hiring Manager.
In terms of race, more HR personnel and hiring managers are white than any other race. Although on pure census demographics, whites are under represented in the total hiring process at both the level of HR and Hiring Manager.
Blacks are over represented at the level of HR personnel and don’t show up at all at the level of Hiring Manager.
As a whole, Asians are over represented at the level of HR personnel and Hiring Manager. At the HR level, their over-representation is 3-fold (19%) their representation in the US population (5.6%).  At the level of Hiring Manager, their representation (47%) is about 8 times their representation (5.9%) in the general US population. That’s an 800% difference.
The Hispanic population is sorely under represented in both aspects of the hiring process. Of the 53 people I encountered in this round of applications, I only identified 3 as Hispanic.
My cheeky conclusion is this. We live in a world where what you look like matters, and most people are on a crusade to maintain a certain comfort level in most aspects of their life including hiring decisions. Thus, if you’re looking for a medical information job in pharma, it still pays to be white and in a twist of events, female as well. And if you can’t be white, be Asian, in particular Indian.
*mic drop*

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