• There are results analysed by the users of our Chrome extension.

How diverse are Engineering teams?

3%
3% of the teams analysed have no Black people in their teams (2 out of 80)
29%
29% of the teams analysed have no Black Women in their teams (23 out of 80)
22%
Overall 22% of all the teams analysed are women (5970 out of 27428 people)
1%
Overall 1% of all the teams analysed are Black Women (154 out of 27428 people)

Order by:
NameWomenBlackBlack Women
55%
60 people
6%
6 people
1%
1 person
47%
103 people
5%
10 people
2%
4 people
32%
162 people
7%
37 people
2%
9 people
32%
47 people
3%
4 people
1%
1 person
32%
38 people
3%
4 people
0%
0 people
32%
77 people
3%
7 people
0%
0 people
31%
34 people
2%
2 people
0%
0 people
31%
107 people
7%
23 people
1%
5 people
30%
46 people
3%
5 people
0%
0 people
30%
192 people
6%
37 people
2%
11 people
29%
40 people
5%
7 people
1%
1 person
29%
33 people
4%
4 people
1%
1 person
29%
57 people
4%
7 people
2%
3 people
28%
33 people
1%
1 person
0%
0 people
28%
31 people
5%
5 people
2%
2 people
28%
77 people
3%
8 people
1%
2 people
28%
28 people
18%
18 people
2%
2 people
28%
250 people
6%
53 people
1%
8 people
28%
97 people
3%
11 people
0%
1 person
27%
100 people
3%
10 people
1%
2 people
27%
110 people
4%
15 people
0%
2 people
26%
191 people
2%
17 people
0%
1 person
26%
22 people
3%
3 people
1%
1 person
26%
47 people
2%
4 people
0%
0 people
25%
55 people
4%
8 people
1%
2 people
25%
26 people
2%
2 people
0%
0 people
25%
30 people
9%
11 people
0%
0 people
25%
134 people
5%
25 people
0%
1 person
25%
54 people
0%
0 people
0%
0 people
25%
122 people
3%
17 people
1%
4 people
24%
209 people
3%
25 people
0%
4 people
24%
57 people
7%
17 people
1%
3 people
24%
50 people
9%
18 people
1%
2 people
24%
144 people
3%
19 people
0%
0 people
23%
82 people
5%
16 people
1%
2 people
23%
61 people
2%
6 people
0%
0 people
23%
21 people
2%
2 people
2%
2 people
23%
84 people
2%
7 people
0%
1 person
23%
104 people
3%
16 people
0%
1 person
23%
61 people
3%
9 people
0%
1 person
23%
138 people
3%
18 people
1%
5 people
22%
35 people
3%
5 people
2%
3 people
22%
100 people
5%
25 people
1%
4 people
22%
51 people
2%
5 people
0%
0 people
22%
57 people
5%
12 people
2%
4 people
21%
107 people
2%
9 people
1%
3 people
21%
87 people
3%
11 people
0%
2 people
21%
24 people
2%
2 people
0%
0 people
20%
139 people
4%
27 people
0%
3 people
20%
51 people
4%
10 people
3%
7 people
20%
41 people
2%
5 people
0%
1 person
20%
83 people
3%
14 people
0%
2 people
20%
139 people
3%
22 people
1%
4 people
20%
17 people
2%
2 people
0%
0 people
20%
39 people
7%
14 people
1%
2 people
19%
51 people
3%
7 people
0%
1 person
19%
176 people
4%
41 people
1%
8 people
19%
68 people
4%
16 people
0%
1 person
19%
13 people
0%
0 people
0%
0 people
18%
105 people
2%
11 people
1%
3 people
17%
37 people
2%
4 people
0%
0 people
17%
92 people
3%
15 people
0%
2 people
17%
77 people
4%
16 people
0%
1 person
17%
26 people
3%
5 people
0%
0 people
17%
31 people
2%
3 people
0%
0 people
16%
30 people
4%
8 people
1%
1 person
16%
80 people
4%
18 people
0%
1 person
16%
110 people
4%
27 people
0%
0 people
16%
153 people
2%
21 people
0%
4 people
16%
34 people
0%
1 person
0%
0 people
15%
140 people
2%
22 people
0%
3 people
15%
139 people
2%
22 people
0%
2 people
14%
30 people
6%
12 people
1%
2 people
13%
13 people
2%
2 people
0%
0 people
13%
12 people
9%
8 people
1%
1 person
13%
23 people
1%
2 people
1%
1 person
12%
16 people
3%
4 people
0%
0 people
11%
61 people
2%
10 people
0%
1 person
11%
59 people
2%
8 people
0%
2 people
10%
10 people
2%
2 people
0%
0 people
How diverse is?
Engineering teamsNon-ProfitMediaGovernmentScottish companies 🏴󠁧󠁢󠁳󠁣󠁴󠁿DigitalSportsBig Tech LeadershipTop UK VC FundsArtificial IntelligenceLeadership teamsFintechBankingCoding Bootcamps
in beta (testing), some things might still be broken
Developed by
nyala.dev logo
Why we built HowDiverse?
This project began when a member of the nyala.dev team received an invitation from a prominent British tech unicorn to apply for one of their job openings. Despite the company's stated commitment to promoting diversity and inclusion, a review of their "about us" page revealed a significant lack of racial diversity among their employees' photos. This discovery sparked the creation of HowDiverse.is as a somewhat tongue-in-cheek side project aimed at pointing out the contradictions in the Diversity, Equity, and Inclusion (DEI) conversation within the tech industry.

We quickly realised that our side project could have a more significant impact beyond the tech industry. For those organisations genuinely dedicated to DEI, the starting point must be transparency, which in turn fosters accountability and tangible actions. This is the ultimate goal of HowDiverse.is: to develop tools and provide open data that empower a DEI dialogue that transcends mere corporate checkboxes.

Want to analyse websites yourself?

We just released a Chrome extension that lets you analyze any website with a lot more features. No need to enter the URL on our website anymore. Plus, you can analyze internal or protected pages too.

Go ahead and download the extension now. Give it a spin!

Download the Chrome Extension
How does it work?
  1. Download the Chrome Extension
  2. Go to a website (i.e. the careers page or who we are pages of a company) and open the extension
  3. We extract all the images from the page
  4. We automagically detect all the faces in those images
  5. We run gender and ethnicity analysis using Artificial Intelligence (Deep Learning)*
  6. We generate a report with the result.
* We also regularly check the results manually to improve the model because AI, ironically, is racist and lacks diversity.